A system for detecting borate saturation and a control method thereof

Abstract

This application relates to the field of boric acid detection technology, and in particular to a system for detecting boric acid saturation and its control method. It includes: setting multiple detection time nodes based on production needs; introducing the boric acid solution to be tested from the main production line into a connected detection pool via branch pipelines at each detection time node; acquiring the characteristic spectrum of the boric acid solution to be tested in the connected detection pool; setting the control parameters of the thermal detection unit based on the characteristic spectrum and a preset detection control model; acquiring feedback images from the connected detection pool; and generating the saturation detection result of the boric acid solution to be tested based on all feedback images and a preset precipitation temperature-concentration mapping curve. By adding a connected detection pool to introduce the boric acid solution to be tested from the main production line, the real-time performance of the detection is improved, providing data support for adjusting the production process of boric acid fertilizer. Simultaneously, by establishing a dual detection mechanism, the detection adaptability efficiency under different production scenarios is improved.

Description

Technical Field

[0001] This application relates to the field of boric acid detection technology, and in particular to a system for detecting boric acid saturation and a method for controlling it. Background Technology

[0002] In the actual production of boric acid fertilizer, the saturation of the boric acid solution is a key factor affecting product quality and yield. If the saturation is too high, fine crystals are easily precipitated prematurely, resulting in uneven crystal size and difficulty in filtration; if the saturation is too low, the yield decreases and the burden on the mother liquor circulation increases.

[0003] Currently, most production sites still use manual sampling and offline testing. Operators take samples from the reaction vessel at regular intervals and then determine the concentration using a hydrometer or titration. This method is not only time-consuming, but by the time the test results are available, the operating conditions inside the vessel have often changed, making it difficult to guide timely adjustments. Furthermore, the solution temperature drops and water evaporates during sampling, leading to a discrepancy between the measured concentration and the actual concentration inside the vessel. Using this discrepancy to control the evaporation or crystallization process can easily cause fluctuations in boron content between batches, and even result in substandard products. Summary of the Invention

[0004] The purpose of this application is to provide a system for detecting boric acid saturation and a method for controlling the above-mentioned technical problems, which aims to improve the detection efficiency and accuracy of boric acid solution saturation and ensure the preparation efficiency of boric acid fertilizer.

[0005] In some embodiments of this application, the boric acid solution to be tested is introduced into the main production line by adding a connected detection pool, thereby improving the real-time performance of the detection and providing data support for adjusting the production process of boric acid fertilizer. At the same time, by establishing a dual detection mechanism, the detection adaptation efficiency under different production scenarios is improved.

[0006] In some embodiments of this application, by acquiring the characteristic spectrum of the boric acid solution to be tested, the approximate concentration range of the solution can be quickly inferred. Then, based on the detection control model, the corresponding target precipitation temperature range and gradient temperature control strategy can be selected to improve the saturation detection efficiency and accuracy of the boric acid solution.

[0007] In some embodiments of this application, a control method for a boric acid saturation detection system is provided, including: Multiple testing time nodes are set based on production needs. At each testing time node, the boric acid solution to be tested from the main production line is introduced into the interconnected testing pool through branch pipelines. Obtain the characteristic spectrum of the boric acid solution to be tested in the connected detection cell, and set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model; The feedback images within the connected detection cell are acquired, and the saturation detection result of the boric acid solution to be tested is generated based on all the feedback images and the preset precipitation temperature-concentration mapping curve.

[0008] In some embodiments of this application, the preset detection control model includes: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: a precipitation temperature range and a gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

[0009] In some embodiments of this application, the setting of control parameters for the thermal detection unit includes: Obtain the operating temperature of the main production line; Based on the operating temperature setting, the acquisition command and spectral analysis model are set, and the characteristic spectrum of the boric acid solution to be detected is obtained according to the current acquisition command. The feature spectrum is input into the spectral analysis model, and the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model is generated based on the output results. The expected concentration range is selected based on the total similarity, and the control parameters of the thermal detection unit are set according to the expected concentration range.

[0010] In some embodiments of this application, the control parameters of the thermal detection unit are set according to the expected concentration range, including: Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; A first cooling range and a second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes of the first cooling range are set based on the cooling evaluation value; The first-level control command for the first cooling range is set according to the cooling rate and all temperature nodes; Based on the target temperature control strategy, multiple feedback nodes are selected within the second cooling range, and secondary control commands for the second cooling range are set based on all feedback nodes.

[0011] In some embodiments of this application, the primary control instructions include: Obtain a subset of monitoring images for the current temperature node, wherein the subset of monitoring images includes: multiple frames of monitoring images; The crystallization anomaly value for the current temperature node is generated based on the subset of the monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

[0012] In some embodiments of this application, the acquisition of feedback images within the connectivity detection pool includes: Set the reference temperature node according to the second cooling range; The real-time temperature in the connected detection pool is obtained, and when the real-time temperature reaches the reference temperature node, a subset of reference images is generated. A reference frame image is established based on the preprocessing results of the reference image subset; Execute secondary control commands and generate a subset of feedback images for each feedback node; The single feedback image subset includes: multiple consecutive frames of feedback images.

[0013] In some embodiments of this application, generating the saturation detection result of the boric acid solution to be tested includes: Set the subset of feedback images from the current feedback node as the subset to be analyzed; In the subset to be analyzed, single-frame feedback images are selected sequentially and set as images to be analyzed. Generate a difference image between the image to be analyzed and the reference frame image, and generate a subset of the crystal nuclei of the image to be analyzed based on the processing result of the difference image; Generate a subset of crystal nuclei for each feedback image in the subset to be analyzed, and select a precipitated frame image based on all the subsets of crystal nuclei; The saturation detection result of the boric acid solution to be tested is generated based on the temperature parameters corresponding to the precipitation frame image and the preset precipitation temperature-concentration mapping curve.

[0014] In some embodiments of this application, a system for detecting boric acid saturation is provided, comprising: The testing pool is connected to the main production line via a branch pipeline. The connected detection pool is used to store the boric acid solution to be tested from the main production line; Optical auxiliary unit, including spectral submodule and image submodule; The spectral submodule is used to acquire the characteristic spectrum of the boric acid solution to be tested; The image submodule is used to acquire image data of the boric acid solution to be detected; The thermal detection unit includes a temperature control submodule and a monitoring submodule; The temperature control submodule is used to control the temperature inside the connected detection pool; The monitoring submodule is used to collect temperature data inside the connected detection pool; The central control unit includes: The first processing module is used to set multiple detection time nodes according to production needs, and introduce the boric acid solution to be tested from the main production line into the connected detection pool through branch pipelines at each detection time node. The second processing module is used to acquire the characteristic spectrum of the boric acid solution to be detected in the connected detection cell, and to set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model. The third processing module is used to acquire feedback images in the connected detection cell and generate the saturation detection result of the boric acid solution to be tested based on all feedback images and the preset precipitation temperature-concentration mapping curve.

[0015] In some embodiments of this application, the second processing module is further configured to: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: a precipitation temperature range and a gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

[0016] In some embodiments of this application, the second processing module is further configured to: Obtain the operating temperature of the main production line; Based on the operating temperature setting, the acquisition command and spectral analysis model are set, and the characteristic spectrum of the boric acid solution to be detected is obtained according to the current acquisition command. The feature spectrum is input into the spectral analysis model, and the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model is generated based on the output results. Select the expected concentration range based on all similarities; Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; A first cooling range and a second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes of the first cooling range are set based on the cooling evaluation value; The first-level control command for the first cooling range is set according to the cooling rate and all temperature nodes; According to the target temperature control strategy, multiple feedback nodes are selected in the second cooling range, and secondary control commands for the second cooling range are set according to all feedback nodes. The first-level control commands include: Obtain a subset of monitoring images for the current temperature node, wherein the subset of monitoring images includes: multiple frames of monitoring images; The crystallization anomaly value for the current temperature node is generated based on the subset of the monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

[0017] Compared with the prior art, the boric acid saturation detection system and control method of this application have the following advantages: By adding a connected detection pool to introduce the boric acid solution to be tested into the main production line, the real-time performance of the detection is improved, providing data support for the adjustment of the boric acid fertilizer production process. At the same time, by establishing a dual detection mechanism, the detection adaptation efficiency under different production scenarios is improved.

[0018] By acquiring the characteristic spectrum of the boric acid solution to be tested, the approximate concentration range of the solution can be quickly inferred. Based on the detection control model, the corresponding target precipitation temperature range and gradient temperature control strategy can be selected to improve the detection efficiency and accuracy of boric acid solution saturation. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a control method for a boric acid saturation detection system in a preferred embodiment of this application.

[0020] Figure 2 This is a schematic diagram of a boric acid saturation detection system in a preferred embodiment of this application. Detailed Implementation

[0021] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0022] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0024] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0025] like Figure 1 As shown in the preferred embodiment of this application, a control method for a boric acid saturation detection system includes: S101: Based on production needs, multiple testing time nodes are set, and the boric acid solution to be tested from the main production line is introduced into the connected testing pool through branch pipelines at each testing time node. S102: Obtain the characteristic spectrum of the boric acid solution to be tested in the connected detection cell, and set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model; S103: Acquire feedback images within the connected detection cell, and generate saturation detection results for the boric acid solution to be tested based on all feedback images and the preset precipitation temperature-concentration mapping curve.

[0026] Specifically, based on the production process of boric acid fertilizer, select the time period for saturation testing, such as the solution evaporation and concentration process, crystallization process, etc., and select multiple testing time points according to the selected time period.

[0027] Specifically, the interconnection detection pool is preferably a sealed, pressure-resistant, transparent pool. It is connected to the main production line (i.e., the main conveying line of boric acid solution) through a branch pipeline. The pressure of the conveying pump on the main production line is used to allow a small amount of boric acid solution to be tested to flow into the interconnection detection pool through the branch pipeline.

[0028] Specifically, the thermal detection unit is preferably a device equipped with a heating structure and a temperature sensor. The thermal detection unit is installed close to the outside of the connected detection pool to control the temperature of the boric acid solution to be tested in the connected detection pool.

[0029] Specifically, a precipitation temperature-concentration mapping curve was constructed using experimental data, including the precipitation temperature values ​​corresponding to boric acid solutions of different concentrations.

[0030] Specifically, the preset detection and control model includes: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: precipitation temperature range and gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

[0031] Specifically, the concentration range of boric acid solution is set according to the historical production parameters of boric acid fertilizer, and the concentration range is uniformly divided to set multiple concentration intervals. The granularity of the concentration range is set according to the spectral scanning accuracy and the actual noise to avoid overlapping spectral features (for example, when the detection concentration difference of spectral scanning is 0.2% to 0.5%, the width of a single concentration interval can be set to 1.5% to 3.0%).

[0032] Specifically, based on the solubility value corresponding to the target concentration range and the precipitation temperature-concentration mapping curve, the precipitation temperature range of the target concentration range is selected (first, the basic temperature range is determined based on the precipitation temperatures corresponding to the concentration values ​​at the two endpoints of the target concentration range, and then a safe temperature range is added to generate the precipitation temperature range. For example, if the precipitation temperatures corresponding to the concentration values ​​at the two endpoints of the target concentration range are 45℃ and 60℃, the basic temperature range is set to 45℃-60℃, and then extended by 3℃ above and below as a safe boundary, thus setting the precipitation temperature range of the target concentration range to 42℃-63℃).

[0033] Specifically, by analyzing the historical production parameters of boric acid fertilizer, the optimal gradient cooling parameters are set within the corresponding precipitation temperature range for the target concentration range. These gradient cooling parameters include the cooling rate and the feedback node interval (e.g., cooling rate 0.5℃ / min, node interval 1℃). Based on the optimal gradient cooling parameters, a gradient temperature control strategy for the target concentration range is set.

[0034] Specifically, an operating temperature range (i.e., the temperature of the boric acid solution during the production process) is generated based on the historical production parameters of boric acid fertilizer. The operating temperature range is then uniformly divided, and multiple basic temperature ranges are set (the length of a single basic temperature range can be set according to the degree of interference of temperature on the characteristic spectral parameters of the boric acid solution; the greater the degree of interference, the smaller the length of the corresponding single basic temperature range). Within a single basic temperature range, the characteristic spectral parameters of the boric acid solution will not change significantly due to temperature fluctuations.

[0035] Specifically, characteristic spectra of boric acid solutions at multiple concentration points within the current concentration range are collected (using a high-sensitivity spectrometer), and various characteristic indices of all characteristic spectra are fitted to generate the spectral mapping state of the current concentration range in the target temperature range. The spectral mapping state refers to the value range corresponding to each characteristic index. Among them, the characteristic indices include: characteristic peak absorbance ratio, characteristic peak absorption bandwidth, water molecule characteristic peak offset, spectral baseline tilt, and other parameters related to the concentration value.

[0036] It is understandable that in the above embodiments, by adding a connected detection pool to introduce the boric acid solution to be tested into the main production line, the real-time performance of the detection is improved. At the same time, by constructing a detection control model, it is adapted to different boric acid fertilizer production scenarios, thereby improving the overall detection accuracy and providing data support for the adjustment of the boric acid fertilizer production process.

[0037] In a preferred embodiment of this application, the control parameters for the thermal detection unit are set, including: Obtain the operating temperature of the main production line; The acquisition command and spectral analysis model are set according to the operating temperature, and the characteristic spectrum of the boric acid solution to be tested is obtained according to the current acquisition command. Input the feature spectrum into the spectral analysis model, and generate the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model based on the output results; The expected concentration range is selected based on the overall similarity; and the control parameters of the thermal detection unit are set according to the expected concentration range.

[0038] Specifically, the operating temperature of the main production line refers to the temperature of the boric acid solution to be tested in the main production line.

[0039] Specifically, the acquisition command means that after the boric acid solution to be tested is introduced into the connected detection pool from the main production line, the temperature of the boric acid solution to be tested is first adjusted to the operating temperature of the main production line through active temperature regulation, and then the corresponding characteristic spectrum is acquired using the spectral submodule (i.e., high-sensitivity spectrometer), thereby ensuring the accuracy of the acquired data and avoiding interference with the detection results due to temperature fluctuations of the boric acid solution to be tested during the introduction process.

[0040] Specifically, the analysis sub-model corresponding to the base temperature range where the operating temperature is located is a spectral analysis model.

[0041] Specifically, the acquired characteristic spectra are compared with the spectral mapping states corresponding to each concentration range in the spectral analysis model to generate similarity values ​​for each spectral mapping state. The concentration range corresponding to the maximum value among all similarity values ​​is then set as the expected concentration range of the boron solution to be tested. Generating similarity values ​​means setting corresponding similarity values ​​based on the difference between the real-time parameters of each characteristic index in the acquired characteristic spectra and the value ranges corresponding to each characteristic index in the current spectral mapping state. The smaller the difference, the larger the corresponding similarity value. The mapping relationship between the two can be set based on historical parameters.

[0042] Specifically, the control parameters of the thermal detection unit are set according to the expected concentration range, including: Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; The first cooling range and the second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes for the first cooling zone are set based on the cooling assessment values. The first-level control command for the first cooling zone is set based on the cooling rate and all temperature nodes. Based on the target temperature control strategy, multiple feedback nodes are selected within the second cooling range, and secondary control commands for the second cooling range are set based on all feedback nodes.

[0043] Specifically, the precipitation temperature range corresponding to the expected concentration range is set as the target precipitation temperature range, and the gradient temperature control strategy corresponding to the expected concentration range is set as the target temperature control strategy.

[0044] Specifically, the temperature interval between the operating temperature and the target precipitation temperature range is set as the first cooling range. If the boric acid solution to be detected is in a suspected saturated state during the spectral detection process, the operating temperature will be in the precipitation temperature range corresponding to the expected concentration range. In this case, the first cooling range does not need to be set, and the second cooling range is set directly and the corresponding operation is performed.

[0045] Specifically, a first evaluation value is set based on the length of the first cooling interval. The larger the length, the greater the span of the first cooling interval, and the larger the corresponding first evaluation value. The mapping relationship between the two can be set based on historical parameters. A second evaluation value is set based on the expected concentration range. The smaller the median value of the expected concentration range, the lower the current concentration of boric acid to be detected, and the larger the corresponding second evaluation value. The mapping relationship between the two can be set based on historical parameters, and the value ranges of the first and second evaluation values ​​are the same.

[0046] Specifically, the sum of the first and second evaluation values ​​is set as the cooling evaluation value of the first cooling interval. The larger the cooling evaluation value, the greater the corresponding cooling rate and the larger the interval between adjacent temperature nodes. The specific mapping relationship can be set by analyzing the historical production parameters of boric acid fertilizer.

[0047] Specifically, multiple feedback nodes are set according to the feedback node interval in the target temperature control strategy.

[0048] Specifically, level one control commands include: Obtain a subset of monitoring images for the current temperature node. The subset of monitoring images includes multiple frames of monitoring images. Generate crystallization anomaly values ​​for the current temperature node based on a subset of monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

[0049] Specifically, the image submodule (i.e., a high-sensitivity digital camera) continuously acquires multiple frames of monitoring images, and analyzes these images based on time sequence to determine whether crystals appear due to rapid cooling (each frame is differentiated from the previous frame or the average background to remove stationary blemishes, and each bright spot in the image is automatically identified through brightness and size thresholds to obtain the number of crystals). The more crystals there are, the larger the corresponding crystallization anomaly value. The mapping relationship between the two can be set according to historical parameters.

[0050] Specifically, the crystallization anomaly threshold can be set based on historical parameters. When the real-time crystallization anomaly value is greater than the preset crystallization anomaly threshold, it indicates that the boric acid solution to be tested has experienced local premature precipitation due to excessive cooling. The cooling rate needs to be corrected in time to avoid misjudgment.

[0051] It is understood that in the above embodiments, by acquiring the characteristic spectrum of the boric acid solution to be tested, the approximate concentration range of the solution can be quickly inferred, thereby selecting the corresponding target precipitation temperature range and gradient temperature control strategy according to the detection control model, and improving the detection efficiency and accuracy of boric acid solution saturation.

[0052] In a preferred embodiment of this application, acquiring feedback images within the connectivity detection pool includes: Set the reference temperature node according to the second cooling range; The real-time temperature in the connected detection pool is obtained, and when the real-time temperature reaches the reference temperature node, a subset of reference images is generated. A reference frame image is established based on the preprocessing results of a subset of reference images; Execute secondary control commands and generate a subset of feedback images for each feedback node; The single feedback image subset includes: multiple consecutive frames of feedback images.

[0053] Specifically, the reference temperature node refers to the maximum temperature value in the second cooling interval. When the real-time temperature in the connected detection pool reaches the reference temperature node, it indicates that the operation of the first cooling interval has been completed. At this time, the thermal detection unit is controlled to execute the target temperature control strategy according to the secondary control command.

[0054] Specifically, when at the reference temperature node, multiple frames of image data are collected and fused for analysis to construct a reference frame image (i.e., the image features of the boric acid solution to be tested when no crystals have precipitated). Specifically, after entering the second cooling zone, the image submodule continuously acquires image data within the connected detection pool. When generating each feedback image, it marks the temperature value of the boric acid solution to be detected at the time of acquisition. It also generates a subset of feedback images at each feedback node (which includes all feedback images acquired between the previous and current feedback nodes). The subset of feedback images is then uploaded to the central control unit for analysis to determine the precipitation temperature of the boric acid solution to be detected and the corresponding concentration value. Based on the determined concentration value, the corresponding saturation detection result is generated.

[0055] Specifically, the saturation detection results of the boric acid solution to be tested include: Set the subset of feedback images from the current feedback node as the subset to be analyzed; Select individual frame feedback images sequentially from the subset to be analyzed and set them as the images to be analyzed. Generate a difference image between the image to be analyzed and the reference frame image, and generate a subset of the crystal nuclei of the image to be analyzed based on the processing results of the difference image; Generate a subset of crystal nuclei for each feedback image in the subset to be analyzed, and select the extraction frame image based on the entire subset of crystal nuclei; The saturation detection result of the boric acid solution to be tested is generated based on the temperature parameters corresponding to the precipitation frame image and the preset precipitation temperature-concentration mapping curve.

[0056] Specifically, by performing differential processing on the image to be analyzed and the reference frame image, the gray value of each pixel in the image to be analyzed is subtracted from the gray value of the corresponding pixel in the reference frame image, thereby extracting the pixels with changes for subsequent analysis and judgment. Gaussian smoothing filtering is applied to each differential image to remove random noise, and the remaining pixels are set as a subset of crystal nuclei. Then, based on time-series processing, correlation analysis is performed on each subset of crystal nuclei to select the feedback image corresponding to the first identification of an "effective borate crystal nucleus," which is set as the precipitation frame image. The corresponding concentration value is determined based on the temperature of the precipitation frame image, and the corresponding saturation detection result is generated based on the determined concentration value.

[0057] In another preferred embodiment of the control method for a boric acid saturation detection system based on any of the above preferred embodiments, this preferred embodiment provides a boric acid saturation detection system, comprising: The testing pool is connected to the main production line via a branch pipeline. The interconnected detection pool is used to store the boric acid solution to be tested from the main production line; Optical auxiliary unit, including spectral submodule and image submodule; The spectral submodule is used to acquire the characteristic spectra of the boric acid solution to be tested; The image submodule is used to acquire image data of the boric acid solution to be tested; The thermal detection unit includes a temperature control submodule and a monitoring submodule; The temperature control submodule is used to control the temperature inside the connected detection pool; The monitoring submodule is used to collect temperature data inside the connected detection pool; The central control unit includes: The first processing module is used to set multiple detection time nodes according to production needs, and introduce the boric acid solution to be tested from the main production line into the connected detection pool through branch pipelines at each detection time node. The second processing module is used to acquire the characteristic spectrum of the boric acid solution to be detected in the connected detection cell, and to set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model. The third processing module is used to acquire feedback images in the connected detection cell and generate saturation detection results of the boric acid solution to be tested based on all feedback images and the preset precipitation temperature-concentration mapping curve.

[0058] Specifically, the interconnection detection pool is preferably a sealed, pressure-resistant, transparent pool. It is connected to the main production line (i.e., the main conveying line of boric acid solution) through a branch pipeline. The pressure of the conveying pump on the main production line is used to allow a small amount of boric acid solution to be tested to flow into the interconnection detection pool through the branch pipeline.

[0059] Specifically, the thermal detection unit is preferably a device with a heating structure (i.e., a temperature control submodule) and a temperature sensor (i.e., a monitoring submodule). The thermal detection unit is installed close to the outside of the connected detection pool to control the temperature of the boric acid solution to be tested in the connected detection pool.

[0060] Specifically, the spectral submodule is preferably a high-sensitivity spectrometer, and the image submodule is preferably a high-sensitivity digital camera.

[0061] In a preferred embodiment of this application, the second processing module is further configured to: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: precipitation temperature range and gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

[0062] In a preferred embodiment of this application, the second processing module is further configured to: Obtain the operating temperature of the main production line; The acquisition command and spectral analysis model are set according to the operating temperature, and the characteristic spectrum of the boric acid solution to be tested is obtained according to the current acquisition command. Input the feature spectrum into the spectral analysis model, and generate the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model based on the output results; Select the expected concentration range based on all similarities; Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; The first cooling range and the second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes for the first cooling zone are set based on the cooling assessment values. The first-level control command for the first cooling zone is set based on the cooling rate and all temperature nodes. Based on the target temperature control strategy, multiple feedback nodes are selected in the second cooling zone, and secondary control commands for the second cooling zone are set based on all feedback nodes. Level 1 control commands include: Obtain a subset of monitoring images for the current temperature node. The subset of monitoring images includes multiple frames of monitoring images. Generate crystallization anomaly values ​​for the current temperature node based on a subset of monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

[0063] According to the first concept of this application, by adding a connected detection pool to introduce the boric acid solution to be tested into the main production line, the real-time performance of the detection is improved, providing data support for the adjustment of the boric acid fertilizer production process. At the same time, by establishing a dual detection mechanism, the detection adaptation efficiency under different production scenarios is improved.

[0064] According to the second concept of this application, by collecting the characteristic spectrum of the boric acid solution to be tested, the approximate concentration range of the solution can be quickly inferred. Then, based on the detection control model, the corresponding target precipitation temperature range and gradient temperature control strategy can be selected to improve the saturation detection efficiency and accuracy of the boric acid solution.

[0065] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. A control method of a borate saturation system characterized by, include: Multiple testing time nodes are set based on production needs. At each testing time node, the boric acid solution to be tested from the main production line is introduced into the interconnected testing pool through branch pipelines. Obtain the characteristic spectrum of the boric acid solution to be tested in the connected detection cell, and set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model; The feedback images within the connected detection cell are acquired, and the saturation detection result of the boric acid solution to be tested is generated based on all the feedback images and the preset precipitation temperature-concentration mapping curve.

2. The control method for the boric acid saturation detection system as described in claim 1, characterized in that, The preset detection and control model includes: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: a precipitation temperature range and a gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

3. The control method for the boric acid saturation detection system as described in claim 2, characterized in that, The control parameters for setting the thermal detection unit include: Obtain the operating temperature of the main production line; Based on the operating temperature setting, the acquisition command and spectral analysis model are set, and the characteristic spectrum of the boric acid solution to be detected is obtained according to the current acquisition command. The feature spectrum is input into the spectral analysis model, and the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model is generated based on the output results. The expected concentration range is selected based on the total similarity, and the control parameters of the thermal detection unit are set according to the expected concentration range.

4. The control method for the boric acid saturation detection system as described in claim 3, characterized in that, The control parameters of the thermal detection unit are set according to the expected concentration range, including: Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; A first cooling range and a second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes of the first cooling range are set based on the cooling evaluation value; The first-level control command for the first cooling range is set according to the cooling rate and all temperature nodes; Based on the target temperature control strategy, multiple feedback nodes are selected within the second cooling range, and secondary control commands for the second cooling range are set based on all feedback nodes.

5. The control method for the boric acid saturation detection system as described in claim 4, characterized in that, The first-level control commands include: Obtain a subset of monitoring images for the current temperature node, wherein the subset of monitoring images includes: multiple frames of monitoring images; The crystallization anomaly value for the current temperature node is generated based on the subset of the monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

6. The control method for the boric acid saturation detection system as described in claim 4, characterized in that, Acquire feedback images within the connectivity detection pool, including: Set the reference temperature node according to the second cooling range; The real-time temperature in the connected detection pool is obtained, and when the real-time temperature reaches the reference temperature node, a subset of reference images is generated. A reference frame image is established based on the preprocessing results of the reference image subset; Execute secondary control commands and generate a subset of feedback images for each feedback node; The single feedback image subset includes: multiple consecutive frames of feedback images.

7. The control method for the boric acid saturation detection system as described in claim 6, characterized in that, Generating the saturation detection result of the boric acid solution to be tested includes: Set the subset of feedback images from the current feedback node as the subset to be analyzed; In the subset to be analyzed, single-frame feedback images are selected sequentially and set as images to be analyzed. Generate a difference image between the image to be analyzed and the reference frame image, and generate a subset of the crystal nuclei of the image to be analyzed based on the processing result of the difference image; Generate a subset of crystal nuclei for each feedback image in the subset to be analyzed, and select a precipitated frame image based on all the subsets of crystal nuclei; The saturation detection result of the boric acid solution to be tested is generated based on the temperature parameters corresponding to the precipitation frame image and the preset precipitation temperature-concentration mapping curve.

8. A system for detecting boric acid saturation, employing the control method for the boric acid saturation detection system according to any one of claims 1-7, characterized in that, include: The testing pool is connected to the main production line via a branch pipeline. The connected detection pool is used to store the boric acid solution to be tested from the main production line; Optical auxiliary unit, including spectral submodule and image submodule; The spectral submodule is used to acquire the characteristic spectrum of the boric acid solution to be tested; The image submodule is used to acquire image data of the boric acid solution to be detected; The thermal detection unit includes a temperature control submodule and a monitoring submodule; The temperature control submodule is used to control the temperature inside the connected detection pool; The monitoring submodule is used to collect temperature data inside the connected detection pool; The central control unit includes: The first processing module is used to set multiple detection time nodes according to production needs, and introduce the boric acid solution to be tested from the main production line into the connected detection pool through branch pipelines at each detection time node. The second processing module is used to acquire the characteristic spectrum of the boric acid solution to be detected in the connected detection cell, and to set the control parameters of the thermal detection unit according to the characteristic spectrum and the preset detection control model. The third processing module is used to acquire feedback images in the connected detection cell and generate the saturation detection result of the boric acid solution to be tested based on all feedback images and the preset precipitation temperature-concentration mapping curve.

9. The boric acid saturation detection system as described in claim 8, characterized in that, The second processing module is further configured to: Multiple concentration ranges can be preset; Select the target concentration range sequentially from all concentration ranges and establish a control sub-model for the target concentration range; The control sub-model includes: a precipitation temperature range and a gradient temperature control strategy; Control sub-models for each concentration range are set sequentially; Multiple base temperature ranges are preset, and the target temperature range is selected sequentially from all base temperature ranges; Define the spectral mapping state of each concentration range in the target temperature range, and define the analysis sub-model of the target temperature range based on all spectral mapping states; The analysis sub-models for each basic temperature range are generated sequentially; A detection control model is established based on all control sub-models and all analysis sub-models.

10. The boric acid saturation detection system as described in claim 9, characterized in that, The second processing module is also used for: Obtain the operating temperature of the main production line; Based on the operating temperature setting, the acquisition command and spectral analysis model are set, and the characteristic spectrum of the boric acid solution to be detected is obtained according to the current acquisition command. The feature spectrum is input into the spectral analysis model, and the similarity between the feature spectrum and each spectral mapping state in the spectral analysis model is generated based on the output results. Select the expected concentration range based on all similarities; Select the target precipitation temperature range and target temperature control strategy based on the expected concentration range; A first cooling range and a second cooling range are set according to the operating temperature and the target precipitation temperature range; Generate the cooling assessment value for the first cooling range; The cooling rate and multiple temperature nodes of the first cooling range are set based on the cooling evaluation value; The first-level control command for the first cooling range is set according to the cooling rate and all temperature nodes; According to the target temperature control strategy, multiple feedback nodes are selected in the second cooling range, and secondary control commands for the second cooling range are set according to all feedback nodes. The first-level control commands include: Obtain a subset of monitoring images for the current temperature node, wherein the subset of monitoring images includes: multiple frames of monitoring images; The crystallization anomaly value for the current temperature node is generated based on the subset of the monitored images; If the crystallization anomaly value is greater than the preset crystallization anomaly value threshold, a correction parameter for the cooling rate is set at the current temperature node.

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