Multi-objective integrated optimization method for large-scale low-cost dry separation system

Abstract

The present application relates to the technical field of dry separation, and discloses a multi-target integrated optimization method of a large-scale low-cost dry separation system, which comprises the following steps: analyzing material parameters, determining an initial air supply amount of a to-be-monitored separator and an initial air supply proportion of a separation area based on the analysis result; judging whether to adjust the initial air supply amount according to historical separation records; when it is determined to adjust the initial air supply amount, adjusting the initial air supply amount based on a real-time bed thickness and a medium density in the bed, and obtaining a final air supply amount; judging whether to adjust the initial air supply proportion according to a real-time material feeding amount; and when it is determined to adjust the initial air supply proportion, adjusting the initial air supply proportion based on a partition pressure drop and a real-time separation effect index, and obtaining a final air supply proportion. The present application can reasonably adjust air supply for materials with different particle sizes and water contents, realize efficient separation, and make product quality stable and reliable.

Description

Technical Field

[0001] This invention relates to the field of dry sorting technology, and more specifically, to a multi-objective integrated optimization method for a large-scale, low-cost dry sorting system. Background Technology

[0002] Traditional dry sorting systems suffer from several problems. Firstly, small-scale dry sorting systems are inefficient when handling large quantities of materials, failing to meet the demands of industrial production. Their limited processing capacity leads to slow material sorting speeds, long production cycles, and increased time costs. Secondly, existing dry sorting systems are often expensive, primarily due to equipment purchase, energy consumption, and maintenance. Some advanced sorting equipment is prohibitively expensive, representing a significant expense for businesses. Furthermore, ensuring effective sorting during operation requires substantial energy consumption, further increasing production costs.

[0003] Furthermore, traditional dry sorting systems have relatively singular objectives, typically optimizing only one or a few indicators, making it difficult to achieve integrated optimization of multiple objectives. For example, pursuing high sorting accuracy may sacrifice sorting efficiency; conversely, improving sorting efficiency may reduce sorting purity. This single-objective optimization approach cannot adapt to complex and ever-changing production demands and cannot achieve a balance between cost and benefit in large-scale production.

[0004] Therefore, it is necessary to design a multi-objective integrated optimization method for large-scale, low-cost dry sorting systems to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes a multi-objective integrated optimization method for large-scale low-cost dry sorting systems, which aims to solve the problem that traditional dry sorting systems have relatively single objectives and can usually only optimize one or a few indicators, making it difficult to achieve multi-objective integrated optimization.

[0006] This invention proposes a multi-objective integrated optimization method for a large-scale, low-cost dry sorting system, comprising the following steps:

[0007] The sorting machine to be monitored, the sorting area, and the material to be sorted are determined. The material parameters of the material to be sorted are collected and analyzed. Based on the analysis results, the initial air supply of the sorting machine to be monitored and the initial air supply ratio of the sorting area are determined.

[0008] Collect the historical sorting records of the sorting machine to be monitored, and determine whether to adjust the initial air supply based on the historical sorting records;

[0009] When it is determined that the initial air supply volume needs to be adjusted, the real-time thickness of the bed and the density of the medium inside the bed of the sorting machine to be monitored are collected. The initial air supply volume is adjusted based on the real-time thickness of the bed and the density of the medium inside the bed, and the final air supply volume is obtained.

[0010] The materials to be sorted are sorted using the final air supply volume and the initial air supply ratio. The real-time material feed volume entering each sorting area is collected, and it is determined whether to adjust the initial air supply ratio based on the real-time material feed volume.

[0011] When it is determined that the initial air supply ratio needs to be adjusted, the zone pressure drop and real-time sorting effect index of each sorting area are collected. Based on the zone pressure drop and real-time sorting effect index, the initial air supply ratio is adjusted to obtain the final air supply ratio.

[0012] Furthermore, when determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the analysis results, the following steps are included:

[0013] The material parameters are analyzed to obtain the particle size characteristic value and moisture content characteristic value of the material to be sorted.

[0014] Obtain the standard values ​​of material particle size and material moisture content corresponding to the material particle size characteristic value and material moisture content characteristic value, respectively;

[0015] The ratio of the material particle size characteristic value to the material particle size standard value is obtained and denoted as the particle size ratio.

[0016] The ratio of the characteristic value of the moisture content of the material to the standard value of the moisture content of the material is obtained and recorded as the moisture content ratio.

[0017] The degree of separation deviation of the separator to be monitored is determined based on the particle size ratio and moisture content ratio.

[0018] The initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area are determined based on the degree of sorting deviation.

[0019] Further, when determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the degree of sorting deviation, the following steps are included:

[0020] The degree of sorting deviation is compared with the first degree of sorting deviation and the second degree of sorting deviation, and the initial air supply volume and the initial air supply ratio are determined based on the comparison result; wherein, the first degree of sorting deviation is less than the second degree of sorting deviation;

[0021] When the degree of sorting deviation is less than or equal to the degree of sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the first air supply volume and the first air supply ratio, respectively.

[0022] When the sorting deviation is greater than the first sorting deviation and less than or equal to the second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the second air supply volume and the second air supply ratio, respectively.

[0023] When the sorting deviation is the second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the third air supply volume and the third air supply ratio, respectively.

[0024] Furthermore, when determining whether to adjust the initial air supply based on the historical sorting records, the process includes:

[0025] The historical sorting records are parsed to obtain the historical sorting records related to abnormal air supply within a preset time window, which are recorded as historical abnormal sorting records.

[0026] Obtain the total number of all the aforementioned historical anomaly sorting records, and record it as the number of historical anomalies;

[0027] Obtain the historical sorting effect index corresponding to each of the historical abnormal sorting records, and obtain the proportion of the abnormal sorting effect index to all the historical sorting effect indicators, which is denoted as the historical abnormal index ratio.

[0028] The initial air supply volume should be adjusted based on the ratio of the number of historical anomalies to the historical anomaly index.

[0029] Furthermore, when determining whether to adjust the initial air supply based on the ratio of the number of historical anomalies to the historical anomaly index, the following steps are included:

[0030] The number of historical anomalies is compared with the threshold number of historical anomalies, and the ratio of historical anomaly indicators is compared with the threshold value of historical anomaly indicators. Based on the comparison results, it is determined whether to adjust the initial air supply.

[0031] When the number of historical anomalies is less than the threshold for the number of historical anomalies, and the ratio of historical anomaly indicators is less than the threshold for the ratio of historical anomaly indicators, it is determined that the initial air supply volume will not be adjusted.

[0032] Otherwise, it is determined that the initial air supply volume should be adjusted.

[0033] Furthermore, when adjusting the initial air supply based on the real-time thickness of the bed and the density of the medium within the bed, the adjustment includes:

[0034] The real-time thickness of the bed layer is compared with the standard bed layer thickness, and the density of the medium in the bed layer is compared with the density of the medium in the standard bed layer. Based on the comparison results, the air supply adjustment coefficient of the initial air supply volume is determined.

[0035] When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the first air supply adjustment coefficient.

[0036] When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the second air supply adjustment coefficient.

[0037] When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the third air supply adjustment coefficient.

[0038] When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the fourth air supply adjustment coefficient.

[0039] The product of the air supply adjustment coefficient and the initial air supply is taken as the final air supply.

[0040] Further, when determining whether to adjust the initial air supply ratio based on the real-time material feed rate, the following steps are included:

[0041] Obtain the real-time material feed rate corresponding to each sorting area;

[0042] Obtain the preset material feed rate corresponding to each sorting area;

[0043] The absolute value of the difference between the real-time material feed rate and the preset material feed rate is calculated based on the real-time material feed rate and recorded as the absolute material feed rate difference.

[0044] Calculate the comprehensive material feed rate deviation index based on the differences in all absolute material feed rates;

[0045] The initial air supply ratio should be adjusted based on the comprehensive material feed deviation index.

[0046] Furthermore, when determining whether to adjust the initial air supply ratio based on the comprehensive material feed rate deviation index, the following steps are included:

[0047] The comprehensive material feed rate deviation index is compared with the comprehensive material feed rate deviation index threshold, and the initial air supply ratio is adjusted based on the comparison result.

[0048] If the comprehensive material feed rate deviation index exceeds the comprehensive material feed rate deviation index threshold, it is determined that the initial air supply ratio should be adjusted.

[0049] Otherwise, it is determined that the initial air supply ratio will not be adjusted.

[0050] Furthermore, when adjusting the initial air supply ratio based on the zonal pressure drop and real-time sorting effect indicators to obtain the final air supply ratio, the process includes:

[0051] The real-time sorting effect indicators are analyzed to obtain real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality.

[0052] The real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality are normalized respectively to obtain normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality.

[0053] The normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality are weighted and summed to obtain the comprehensive real-time sorting index.

[0054] All the aforementioned zone pressure drop and comprehensive real-time sorting indicators are constructed into a supply air ratio vector group;

[0055] The air supply ratio vector group is compared with the historical air supply ratio adjustment group, and the ratio adjustment coefficient of the initial air supply ratio is determined based on the comparison result.

[0056] When there is a historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the historical air supply ratio adjustment coefficient corresponding to the historical air supply ratio vector group shall be used as the ratio adjustment coefficient.

[0057] When there is no historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the ratio adjustment coefficient is determined according to the air supply ratio vector group.

[0058] The initial air supply ratio is adjusted according to the ratio adjustment coefficient to obtain the final air supply ratio.

[0059] Furthermore, when determining the proportional adjustment coefficient based on the air supply proportional vector set, the following is included:

[0060] Calculate the correlation coefficient between each of the air supply ratio vector groups and each of the historical air supply ratio vector groups, and extract the maximum correlation coefficient.

[0061] The maximum correlation coefficient is compared with a preset ratio adjustment coefficient table, and the ratio adjustment coefficient is determined based on the comparison result.

[0062] Compared with existing technologies, the beneficial effects of this invention are as follows: The multi-objective integrated optimization method for large-scale, low-cost dry sorting systems provided by this invention can precisely control the large-scale, low-cost dry sorting system. Regarding air supply, by analyzing material parameters and combining historical sorting records, real-time bed thickness, and medium density, the initial air supply is determined and adjusted as needed to ensure a reasonable airflow supply and avoid poor sorting results. If the air supply is too small, the material cannot be fully suspended and separated; if it is too large, energy is wasted and accuracy is affected. Regarding the air supply ratio, the initial ratio is adjusted based on the real-time material feed rate, and precisely adjusted in conjunction with zone pressure drop and sorting effect indicators to ensure appropriate airflow distribution in each sorting zone, improving overall sorting efficiency and quality. From a cost perspective, this method avoids energy consumption and resource waste, precisely adjusts the air supply and ratio to reduce equipment operating costs, achieves low-cost operation, improves sorting accuracy and efficiency, reduces secondary sorting, and lowers overall costs. In terms of sorting performance, multi-objective integrated optimization is used to adapt to different material characteristics and working conditions, improve sorting accuracy and quality, and reasonably adjust the air supply for materials with different particle sizes and moisture contents to achieve efficient separation, making the product quality stable and reliable and meeting the needs of different scenarios. Attached Figure Description

[0063] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0064] Figure 1 A flowchart of a multi-objective integrated optimization method for a large-scale, low-cost dry sorting system provided in an embodiment of the present invention. Detailed Implementation

[0065] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0066] See Figure 1As shown in some embodiments of this application, this embodiment provides a multi-objective integrated optimization method for a large-scale, low-cost dry sorting system, including the following steps:

[0067] S100: Determine the sorting machine to be monitored, the sorting area, and the material to be sorted; collect the material parameters of the material to be sorted; analyze the material parameters; and determine the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the analysis results.

[0068] S200: Collect the historical sorting records of the sorting machine to be monitored, and determine whether to adjust the initial air supply based on the historical sorting records;

[0069] S300: When it is determined that the initial air supply volume needs to be adjusted, the real-time thickness of the bed and the density of the medium in the bed of the sorting machine to be monitored are collected, the initial air supply volume is adjusted based on the real-time thickness of the bed and the density of the medium in the bed, and the final air supply volume is obtained.

[0070] S400: The material to be sorted is sorted using the final air supply volume and the initial air supply ratio, the real-time material feed volume entering each sorting area is collected, and it is determined whether to adjust the initial air supply ratio based on the real-time material feed volume.

[0071] S500: When it is determined that the initial air supply ratio needs to be adjusted, the zone pressure drop and real-time sorting effect index of each sorting area are collected, the initial air supply ratio is adjusted based on the zone pressure drop and real-time sorting effect index, and the final air supply ratio is obtained.

[0072] In this embodiment, the separator to be monitored is preferably an air-heavy medium fluidized bed dry separator.

[0073] It is understandable that the multi-objective integrated optimization method for the large-scale, low-cost dry sorting system provided in this embodiment can precisely control the system. Regarding air supply, material parameters are analyzed, and the initial air supply is determined by combining historical sorting records, real-time bed thickness, and medium density, and adjusted as needed to ensure a reasonable airflow supply and avoid poor sorting results. If the air supply is too small, the material cannot be fully suspended and separated; if it is too large, energy is wasted and accuracy is affected. Regarding the air supply ratio, the initial ratio is adjusted based on the real-time material feed rate, and precisely adjusted by combining zone pressure drop and sorting effect indicators to ensure appropriate airflow distribution in each sorting area, improving overall sorting efficiency and quality. From a cost perspective, this method avoids energy consumption and resource waste, precisely adjusts the air supply and ratio to reduce equipment operating costs, achieves low-cost operation, improves sorting accuracy and efficiency, reduces secondary sorting, and lowers overall costs. In terms of sorting performance, multi-objective integrated optimization is used to adapt to different material characteristics and working conditions, improve sorting accuracy and quality, and reasonably adjust the air supply for materials with different particle sizes and moisture contents to achieve efficient separation, making the product quality stable and reliable and meeting the needs of different scenarios.

[0074] Specifically, determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the analysis results includes:

[0075] The material parameters are analyzed to obtain the particle size characteristic value and moisture content characteristic value of the material to be sorted.

[0076] Obtain the standard values ​​of material particle size and material moisture content corresponding to the material particle size characteristic value and material moisture content characteristic value, respectively;

[0077] The ratio of the material particle size characteristic value to the material particle size standard value is obtained and denoted as the particle size ratio.

[0078] The ratio of the characteristic value of the moisture content of the material to the standard value of the moisture content of the material is obtained and recorded as the moisture content ratio.

[0079] The degree of separation deviation of the separator to be monitored is determined based on the particle size ratio and moisture content ratio.

[0080] The initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area are determined based on the degree of sorting deviation.

[0081] In this embodiment, the degree of sorting deviation is obtained by weighting the particle size ratio and the moisture content ratio.

[0082] Understandably, by comparing the material particle size and moisture content characteristic values ​​with their respective standard values, the particle size ratio and moisture content ratio are calculated, thereby determining the degree of sorting deviation. This, in turn, determines the initial air supply volume and initial air supply ratio, fully taking into account the characteristics of the materials to be sorted. Different particle sizes and moisture contents significantly affect the suspension and separation effects of materials during the sorting process. For example, materials with larger particle sizes or higher moisture contents may require a larger air supply volume to achieve sufficient suspension and separation. Determining the air supply parameters based on the degree of sorting deviation allows the sorting system to better adapt to different material characteristics, thereby improving the sorting accuracy.

[0083] Specifically, determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the degree of sorting deviation includes:

[0084] The degree of sorting deviation is compared with the first degree of sorting deviation and the second degree of sorting deviation, and the initial air supply volume and the initial air supply ratio are determined based on the comparison result; wherein, the first degree of sorting deviation is less than the second degree of sorting deviation;

[0085] When the degree of sorting deviation is less than or equal to the degree of sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the first air supply volume and the first air supply ratio, respectively.

[0086] When the sorting deviation is greater than the first sorting deviation and less than or equal to the second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the second air supply volume and the second air supply ratio, respectively.

[0087] When the sorting deviation is the second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the third air supply volume and the third air supply ratio, respectively.

[0088] In this embodiment, the initial air supply volume is in the following order: first air supply volume < second air supply volume < third air supply volume.

[0089] In this embodiment, there are preferably three sorting areas, referred to as the first sorting area, the second sorting area, and the third sorting area. The preferred air supply ratio in the first sorting area, the second sorting area, and the third sorting area is 1:4:5, the preferred air supply ratio is 2:3:5, and the preferred air supply ratio is 3:3:4.

[0090] Understandably, by comparing the degree of sorting deviation with the degrees of deviation in the first and second sorting stages to determine the initial air supply volume and initial air supply ratio, it is possible to achieve precise, tiered control of the air supply parameters. This tiered control method takes into account the actual needs of material sorting under different degrees of sorting deviation.

[0091] Specifically, when determining whether to adjust the initial air supply based on the historical sorting records, the following steps are included:

[0092] The historical sorting records are parsed to obtain the historical sorting records related to abnormal air supply within a preset time window, which are recorded as historical abnormal sorting records.

[0093] Obtain the total number of all the aforementioned historical anomaly sorting records, and record it as the number of historical anomalies;

[0094] Obtain the historical sorting effect index corresponding to each of the historical abnormal sorting records, and obtain the proportion of the abnormal sorting effect index to all the historical sorting effect indicators, which is denoted as the historical abnormal index ratio.

[0095] The initial air supply volume should be adjusted based on the ratio of the number of historical anomalies to the historical anomaly index.

[0096] In this embodiment, historical abnormal sorting records refer to sorting records where the air supply volume deviates from the normal range (abnormal air supply volume) within a preset time window. Historical sorting effect indicators refer to various indicators used to measure the sorting effect during the sorting process, such as sorting accuracy and recovery rate. If there is an abnormal indicator in a historical abnormal sorting record, then the historical sorting effect indicator corresponding to that historical abnormal sorting record is marked as an abnormal sorting effect indicator, and the historical abnormal indicator ratio refers to the proportion of historical abnormal sorting records with abnormal indicators among all historical abnormal sorting records.

[0097] Specifically, when determining whether to adjust the initial air supply based on the ratio of the number of historical anomalies to the historical anomaly index, the following steps are included:

[0098] The number of historical anomalies is compared with the threshold number of historical anomalies, and the ratio of historical anomaly indicators is compared with the threshold value of historical anomaly indicators. Based on the comparison results, it is determined whether to adjust the initial air supply.

[0099] When the number of historical anomalies is less than the threshold for the number of historical anomalies, and the ratio of historical anomaly indicators is less than the threshold for the ratio of historical anomaly indicators, it is determined that the initial air supply volume will not be adjusted.

[0100] Otherwise, it is determined that the initial air supply volume should be adjusted.

[0101] Understandably, comparing the number of historical anomalies and the ratio of historical anomaly indicators with corresponding thresholds to determine whether to adjust the initial air supply allows for full utilization of valuable information from historical sorting records. The number of historical anomalies reflects the frequency of air supply anomalies, while the ratio of historical anomaly indicators reflects the proportion of adverse effects of air supply anomalies on sorting performance. If both are less than the threshold, it indicates that historical air supply anomalies were infrequent and had little impact on sorting performance; maintaining the initial air supply helps avoid system fluctuations. If either condition is not met, it means that the air supply anomaly is severe or has a significant negative impact on sorting performance; adjusting the initial air supply in this case helps improve the stability and effectiveness of the sorting system. In practical applications, the two thresholds can be flexibly adjusted according to production needs and equipment characteristics to achieve optimal sorting performance and cost control.

[0102] Specifically, when adjusting the initial air supply based on the real-time thickness of the bed and the density of the medium within the bed, the following steps are included:

[0103] The real-time thickness of the bed layer is compared with the standard bed layer thickness, and the density of the medium in the bed layer is compared with the density of the medium in the standard bed layer. Based on the comparison results, the air supply adjustment coefficient of the initial air supply volume is determined.

[0104] When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the first air supply adjustment coefficient.

[0105] When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the second air supply adjustment coefficient.

[0106] When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the third air supply adjustment coefficient.

[0107] When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the fourth air supply adjustment coefficient.

[0108] The product of the air supply adjustment coefficient and the initial air supply is taken as the final air supply.

[0109] In this embodiment, the real-time bed thickness refers to the actual thickness of the material bed in the separator to be monitored at the current moment during the sorting process. The density of the medium in the bed refers to the actual density of the medium in the material bed in the separator to be monitored during the sorting process.

[0110] Understandably, the order of the air supply adjustment coefficients is: First air supply adjustment coefficient > Second air supply adjustment coefficient > Third air supply adjustment coefficient > Fourth air supply adjustment coefficient. This is because when both the real-time thickness of the bed and the density of the medium within the bed are large, it means the bed is relatively dense, the gaps between materials are small, and a larger air supply is needed to fully suspend and separate the materials, hence the air supply adjustment coefficient is the largest. Conversely, when both the real-time thickness of the bed and the density of the medium within the bed are small, the bed is relatively loose, the materials are more easily suspended, and a relatively smaller air supply is required, hence the air supply adjustment coefficient is the smallest. By determining the air supply adjustment coefficient based on different combinations of the real-time thickness of the bed and the density of the medium within the bed, and thus obtaining the final air supply, precise adjustment of the air supply can be achieved. This precise adjustment can better adapt to the actual conditions of the bed, ensuring that appropriate airflow is provided to the materials to be sorted under different bed conditions, enabling the materials to achieve optimal suspension and separation during the sorting process.

[0111] Specifically, when determining whether to adjust the initial air supply ratio based on the real-time material feed rate, the following steps are included:

[0112] Obtain the real-time material feed rate corresponding to each sorting area;

[0113] Obtain the preset material feed rate corresponding to each sorting area;

[0114] The absolute value of the difference between the real-time material feed rate and the preset material feed rate is calculated based on the real-time material feed rate and recorded as the absolute material feed rate difference.

[0115] Calculate the comprehensive material feed rate deviation index based on the differences in all absolute material feed rates;

[0116] The initial air supply ratio should be adjusted based on the comprehensive material feed deviation index.

[0117] Understandably, the comprehensive material feed rate deviation index is a comprehensive indicator calculated by weighting the differences in all absolute material feed rates. It can reflect the overall deviation between the real-time material feed rate and the preset material feed rate in each sorting area.

[0118] Specifically, when determining whether to adjust the initial air supply ratio based on the comprehensive material feed rate deviation index, the following steps are included:

[0119] The comprehensive material feed rate deviation index is compared with the comprehensive material feed rate deviation index threshold, and the initial air supply ratio is adjusted based on the comparison result.

[0120] If the comprehensive material feed rate deviation index exceeds the comprehensive material feed rate deviation index threshold, it is determined that the initial air supply ratio should be adjusted.

[0121] Otherwise, it is determined that the initial air supply ratio will not be adjusted.

[0122] Understandably, comparing the overall material feed rate deviation index with a threshold to determine whether to adjust the initial air supply ratio allows for informed decision-making based on the actual deviation of the material feed rate. When the overall material feed rate deviation index exceeds the threshold, it indicates a significant overall deviation between the real-time material feed rate in each sorting zone and the preset value. In this case, the initial air supply ratio may not meet the material sorting requirements. Adjusting the initial air supply ratio can provide each sorting zone with a more suitable airflow, thereby improving the sorting effect. If the overall material feed rate deviation index does not exceed the threshold, it indicates that the current material feed rate deviation is within an acceptable range. Maintaining the initial air supply ratio ensures system stability and avoids unnecessary adjustments that could interfere with the sorting process. This judgment method based on the overall material feed rate deviation index provides a scientific and reasonable basis for adjusting the air supply ratio, further enhancing the accuracy and efficiency of large-scale, low-cost dry sorting systems.

[0123] Specifically, when adjusting the initial air supply ratio based on the zonal pressure drop and real-time sorting effect indicators to obtain the final air supply ratio, the following steps are included:

[0124] The real-time sorting effect indicators are analyzed to obtain real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality.

[0125] The real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality are normalized respectively to obtain normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality.

[0126] The normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality are weighted and summed to obtain the comprehensive real-time sorting index.

[0127] All the aforementioned zone pressure drop and comprehensive real-time sorting indicators are constructed into a supply air ratio vector group;

[0128] The air supply ratio vector group is compared with the historical air supply ratio adjustment group, and the ratio adjustment coefficient of the initial air supply ratio is determined based on the comparison result.

[0129] When there is a historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the historical air supply ratio adjustment coefficient corresponding to the historical air supply ratio vector group shall be used as the ratio adjustment coefficient.

[0130] When there is no historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the ratio adjustment coefficient is determined according to the air supply ratio vector group.

[0131] The initial air supply ratio is adjusted according to the ratio adjustment coefficient to obtain the final air supply ratio.

[0132] Understandably, constructing an air supply ratio vector group using zonal pressure drop and real-time sorting performance indicators, and comparing it with a historical air supply ratio adjustment group to determine the ratio adjustment coefficient, thereby adjusting the initial air supply ratio to obtain the final air supply ratio, allows for comprehensive optimization of the air supply ratio by drawing on historical experience. Different combinations of zonal pressure drop and real-time sorting performance indicators correspond to different material sorting states, and the historical air supply ratio adjustment group records adjustment experience under similar past conditions. When identical historical air supply ratio vector groups exist, directly using the corresponding historical air supply ratio adjustment coefficient allows for quick and accurate adjustment of the air supply ratio; when no identical ones exist, determining the ratio adjustment coefficient based on the air supply ratio vector group also allows for reasonable adjustments based on the current situation. This approach comprehensively considers zonal pressure drop and real-time sorting performance, enabling the final air supply ratio to better adapt to the actual needs of the sorting process, further improving the sorting efficiency and quality of large-scale, low-cost dry sorting systems, while reducing unnecessary resource waste, lowering production costs, and achieving multi-objective integrated optimization.

[0133] Specifically, when determining the proportional adjustment coefficient based on the air supply proportional vector set, the following is included:

[0134] Calculate the correlation coefficient between each of the air supply ratio vector groups and each of the historical air supply ratio vector groups, and extract the maximum correlation coefficient.

[0135] The maximum correlation coefficient is compared with a preset ratio adjustment coefficient table, and the ratio adjustment coefficient is determined based on the comparison result.

[0136] In this embodiment, the correlation coefficient is calculated using Euclidean distance.

[0137] Understandably, the preset ratio adjustment coefficient table is a pre-defined table that records the ratio adjustment coefficients corresponding to different correlation coefficients. This table is derived from the analysis and summarization of a large amount of historical sorting data and experimental results. In large-scale, low-cost dry sorting systems, different correlation coefficients reflect the degree of similarity between the current air supply ratio vector group and the historical air supply ratio vector group. The larger the correlation coefficient, the more similar the current situation is to a certain historical situation. In this case, the corresponding ratio adjustment coefficient in history can be referenced to adjust the current air supply ratio. By comparing the maximum correlation coefficient with the preset ratio adjustment coefficient table, the ratio adjustment coefficient suitable for the current sorting state can be quickly and accurately determined. In this way, the system can adjust the air supply ratio in a timely and reasonable manner according to the actual situation, making the air supply ratio more compatible with the material sorting requirements.

[0138] Understandably, when the initial air supply ratio of the first, second, and third sorting areas is 1:5:8, and the maximum correlation coefficient is 0.8, the corresponding ratio adjustment coefficients α1, α2, and α3 are preferably 0.9, 1.1, and 1.2, respectively. Therefore, when adjusting the initial air supply ratio, the air supply ratio of the first sorting area is adjusted to 1 × 0.9 = 0.9, the air supply ratio of the second sorting area is adjusted to 5 × 1.1 = 5.5, and the air supply ratio of the third sorting area is adjusted to 8 × 1.2 = 9.6. After such adjustments, the air supply ratio of each sorting area can better adapt to the real-time sorting requirements of the materials. In the actual sorting process, the characteristics of the materials and the feeding conditions may change at any time. For example, when the particle size distribution of the material changes, or the moisture content of the material varies, it will affect the sorting effect. At this time, through the above adjustment method, the system can dynamically optimize the air supply ratio. Suppose that in the subsequent sorting process, the particle size of the material in the first sorting area suddenly increases, leading to an increase in the sorting difficulty in that area. The system monitors real-time sorting performance indicators and zone pressure drop, reconstructs the air supply ratio vector group, and compares it with the historical air supply ratio adjustment group. If the new maximum correlation coefficient is 0.85, the corresponding ratio adjustment coefficients α1, α2, and α3 become 1.0, 0.9, and 0.8, respectively. Then, the air supply ratio is adjusted again: the air supply ratio for the first sorting zone is adjusted to 0.9 × 1.0 = 0.9, the air supply ratio for the second sorting zone is adjusted to 5.5 × 0.9 = 4.95, and the air supply ratio for the third sorting zone is adjusted to 9.6 × 0.8 = 7.68. This dynamic adjustment of the air supply ratio enables the large-scale, low-cost dry sorting system to maintain high sorting efficiency and quality under different operating conditions. Simultaneously, by fully utilizing historical sorting data and experimental results, the system avoids blindly adjusting the air supply ratio, reducing unnecessary resource waste and truly achieving multi-objective integrated optimization. Moreover, this adjustment method is highly flexible and adaptable, and can flexibly adjust the air supply parameters according to different production needs and equipment characteristics to achieve the best sorting effect and cost control.

[0139] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0140] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0141] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0142] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-objective integrated optimization method for a large-scale, low-cost dry sorting system, characterized in that, include: The sorting machine to be monitored, the sorting area, and the material to be sorted are determined. The material parameters of the material to be sorted are collected and analyzed. Based on the analysis results, the initial air supply of the sorting machine to be monitored and the initial air supply ratio of the sorting area are determined. Collect the historical sorting records of the sorting machine to be monitored, and determine whether to adjust the initial air supply based on the historical sorting records; When it is determined that the initial air supply volume needs to be adjusted, the real-time thickness of the bed and the density of the medium inside the bed of the sorting machine to be monitored are collected. The initial air supply volume is adjusted based on the real-time thickness of the bed and the density of the medium inside the bed, and the final air supply volume is obtained. The materials to be sorted are sorted using the final air supply volume and the initial air supply ratio. The real-time material feed volume entering each sorting area is collected, and it is determined whether to adjust the initial air supply ratio based on the real-time material feed volume. When it is determined that the initial air supply ratio needs to be adjusted, the zone pressure drop and real-time sorting effect index of each sorting area are collected. The initial air supply ratio is adjusted based on the zone pressure drop and real-time sorting effect index to obtain the final air supply ratio. When determining whether to adjust the initial air supply based on the historical sorting records, the following are included: The historical sorting records are parsed to obtain the historical sorting records related to abnormal air supply within a preset time window, which are recorded as historical abnormal sorting records. Obtain the total number of all the aforementioned historical anomaly sorting records, and record it as the number of historical anomalies; Obtain the historical sorting effect index corresponding to each of the historical abnormal sorting records, and obtain the proportion of the abnormal sorting effect index to all the historical sorting effect indicators, which is denoted as the historical abnormal index ratio. Whether to adjust the initial air supply volume is determined based on the ratio of the number of historical anomalies to the historical anomaly index. When determining whether to adjust the initial air supply based on the ratio of the number of historical anomalies to the historical anomaly index, the following methods are included: The number of historical anomalies is compared with the threshold of the number of historical anomalies, and the ratio of the historical anomaly index is compared with the threshold of the ratio of the historical anomaly index. Based on the comparison results, it is determined whether to adjust the initial air supply. When the number of historical anomalies is less than the threshold for the number of historical anomalies, and the ratio of historical anomaly indicators is less than the threshold for the ratio of historical anomaly indicators, it is determined that the initial air supply volume will not be adjusted. Otherwise, it is determined that the initial air supply volume should be adjusted; When adjusting the initial air supply ratio based on the zonal pressure drop and real-time sorting effect indicators to obtain the final air supply ratio, the following steps are included: The real-time sorting effect indicators are analyzed to obtain real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality. The real-time sorting efficiency, real-time sorting accuracy, and real-time sorting quality are normalized respectively to obtain normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality. The normalized real-time sorting efficiency, normalized real-time sorting accuracy, and normalized real-time sorting quality are weighted and summed to obtain the comprehensive real-time sorting index. All the aforementioned zone pressure drop and comprehensive real-time sorting indicators are constructed into a supply air ratio vector group; The air supply ratio vector group is compared with the historical air supply ratio adjustment group, and the ratio adjustment coefficient of the initial air supply ratio is determined based on the comparison result. When there is a historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the historical air supply ratio adjustment coefficient corresponding to the historical air supply ratio vector group shall be used as the ratio adjustment coefficient. When there is no historical air supply ratio vector group in the historical air supply ratio adjustment group that is the same as the air supply ratio vector group, the ratio adjustment coefficient is determined according to the air supply ratio vector group. The initial air supply ratio is adjusted according to the ratio adjustment coefficient to obtain the final air supply ratio.

2. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 1, characterized in that, When determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the analysis results, the following are included: The material parameters are analyzed to obtain the particle size characteristic value and moisture content characteristic value of the material to be sorted. Obtain the standard values ​​of material particle size and material moisture content corresponding to the material particle size characteristic value and material moisture content characteristic value, respectively; The ratio of the material particle size characteristic value to the material particle size standard value is obtained and denoted as the particle size ratio. The ratio of the characteristic value of the moisture content of the material to the standard value of the moisture content of the material is obtained and recorded as the moisture content ratio. The degree of separation deviation of the separator to be monitored is determined based on the particle size ratio and moisture content ratio. The initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area are determined based on the degree of sorting deviation.

3. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 2, characterized in that, When determining the initial air supply volume of the sorting machine to be monitored and the initial air supply ratio of the sorting area based on the degree of sorting deviation, the following are included: The degree of sorting deviation is compared with the first degree of sorting deviation and the second degree of sorting deviation, and the initial air supply volume and the initial air supply ratio are determined based on the comparison result; wherein, the first degree of sorting deviation is less than the second degree of sorting deviation; When the degree of sorting deviation is less than or equal to the degree of sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the first air supply volume and the first air supply ratio, respectively. When the sorting deviation is greater than the first sorting deviation and less than or equal to the second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the second air supply volume and the second air supply ratio, respectively. When the degree of sorting deviation is greater than the degree of second sorting deviation, the initial air supply volume and the initial air supply ratio are determined to be the third air supply volume and the third air supply ratio, respectively.

4. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 1, characterized in that, When adjusting the initial air supply based on the real-time thickness of the bed and the density of the medium within the bed, the following steps are included: The real-time thickness of the bed layer is compared with the standard bed layer thickness, and the density of the medium in the bed layer is compared with the density of the medium in the standard bed layer. Based on the comparison results, the air supply adjustment coefficient of the initial air supply volume is determined. When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the first air supply adjustment coefficient. When the real-time thickness of the bed layer is greater than or equal to the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the second air supply adjustment coefficient. When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is greater than or equal to the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the third air supply adjustment coefficient. When the real-time thickness of the bed layer is less than the standard bed layer thickness, and the density of the medium in the bed layer is less than the density of the medium in the standard bed layer, the air supply adjustment coefficient is determined to be the fourth air supply adjustment coefficient. The product of the air supply adjustment coefficient and the initial air supply is taken as the final air supply.

5. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 4, characterized in that, When determining whether to adjust the initial air supply ratio based on the real-time material feed rate, the following includes: Obtain the real-time material feed rate corresponding to each sorting area; Obtain the preset material feed rate corresponding to each sorting area; The absolute value of the difference between the real-time material feed rate and the preset material feed rate is calculated based on the real-time material feed rate and recorded as the absolute material feed rate difference. Calculate the comprehensive material feed rate deviation index based on the differences in all absolute material feed rates; The initial air supply ratio should be adjusted based on the comprehensive material feed deviation index.

6. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 5, characterized in that, When determining whether to adjust the initial air supply ratio based on the comprehensive material feed rate deviation index, the following are included: The comprehensive material feed rate deviation index is compared with the comprehensive material feed rate deviation index threshold, and the initial air supply ratio is adjusted based on the comparison result. If the comprehensive material feed rate deviation index exceeds the comprehensive material feed rate deviation index threshold, it is determined that the initial air supply ratio should be adjusted. Otherwise, it is determined that the initial air supply ratio will not be adjusted.

7. The multi-objective integrated optimization method for a large-scale, low-cost dry sorting system according to claim 6, characterized in that, When determining the proportional adjustment coefficient based on the air supply proportional vector set, the following is included: Calculate the correlation coefficient between each of the air supply ratio vector groups and each of the historical air supply ratio vector groups, and extract the maximum correlation coefficient. The maximum correlation coefficient is compared with a preset ratio adjustment coefficient table, and the ratio adjustment coefficient is determined based on the comparison result.

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