A data processing method for resource recovery of materials with low tin content

Abstract

The present invention provides a data processing method for resource recovery of materials with low tin content, belonging to the technical field of data processing. Specifically, it includes: when it is determined that the recovery device does not belong to the target monitoring device according to the constituent data of the change monitoring data of the recovery device and the change correlation between different change monitoring data at different times, based on the recovery rate in the recovery process and the change of the Internet of Things monitoring data of the target monitoring device, and combining with the change of the Internet of Things monitoring data of the recovery device to determine the storage processing strategy of the Internet of Things monitoring data of the recovery device, thereby improving the utilization efficiency of the storage space of production data.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to a data processing method for the resource recovery of materials with low tin content. Background Art

[0002] Materials with low tin content include electronic waste containing tin alloys, electroplating wastewater, tinplate waste, etc. The secondary utilization efficiency of materials with low tin content can be greatly improved through a secondary recovery system. At the same time, in the process of recovery and treatment, how to analyze and process the recovery data and improve the recovery and treatment rate has become an urgent technical problem to be solved.

[0003] In the prior art solutions for analyzing and processing recovery data, Internet of Things monitoring devices are often used to monitor and analyze the recovery data in real time, and the operating state of the recovery and treatment device is adjusted accordingly. Specifically, in the invention patent applications CN202410710272.4 "Unattended Control System, Method, Storage Medium, Device and Program for Solid Wastes" and CN201611254309.9 "Remote Monitoring Device for Waste Recycling and Refining", similar technical solutions are given. However, the above technical solutions have the following defects:

[0004] When recovering and treating materials with low tin content, various methods such as vacuum smelting, electrolytic refining, solvent extraction, and membrane separation are often combined for recovery and treatment. Therefore, this leads to a large amount of data related to the recovery equipment and the Internet of Things monitoring data of the recovery equipment in the recovery and treatment process. Therefore, how to perform targeted data storage management, while reducing the storage pressure of production data, store and process the Internet of Things monitoring data with reference value as much as possible, and provide reference for later process improvement, etc., has become an urgent technical problem to be solved.

[0005] To solve the above technical problems, the present application provides a data processing method for the resource recovery of materials with low tin content. Summary of the Invention

[0006] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0007] Specifically, the present application provides a data processing method for the resource recovery of materials with low tin content, which specifically includes:

[0008] S1 Obtain the recovery rates of materials with low tin content in different recovery and treatment times. When it is determined that the fluctuation of the recovery rate meets the requirements in different recovery and treatment times, proceed to the next step;

[0009] S4 divides the number of recycling processes into different recycling process groups according to the recovery rate, obtains the changes in the IoT monitoring data of the recycling equipment in different recycling process groups at different recycling process times, and determines the change monitoring data of the recycling equipment based on the changes;

[0010] S3 obtains the constituent data of the change monitoring data of the recycling equipment, and combines the change correlation between different change monitoring data at different times. When it is determined that the recycling equipment does not belong to the target monitoring equipment, based on the recovery rate in the recycling process and the changes in the IoT monitoring data of the target monitoring equipment, and combines the changes in the IoT monitoring data of the recycling equipment to determine the storage processing strategy for the IoT monitoring data of the recycling equipment.

[0011] The beneficial effects of the present invention are as follows:

[0012] Based on the constituent data of the change monitoring data of the recycling equipment and the change correlation between different change monitoring data at different times, it is determined whether the recycling equipment belongs to the target monitoring equipment, thereby realizing the screening of recycling equipment with a relatively large proportion of the quantity of change monitoring data. At the same time, it also further realizes the screening of the changes between different change monitoring data that have a certain correlation, and then realizes the screening of target monitoring equipment with a relatively high change probability, and also lays a foundation for generating a differentiated storage management strategy according to the changes in the monitoring data of the recycling equipment.

[0013] Based on the recovery rate in the recycling process, the changes in the IoT monitoring data of the target monitoring equipment, and the changes in the IoT monitoring data of the recycling equipment to determine the storage processing strategy for the IoT monitoring data of the recycling equipment, not only considers the differences in the storage processing requirements of the IoT monitoring data due to the changes in the recovery rate, but also considers the differences in the storage requirements of the IoT monitoring data of other recycling equipment due to the correlation degree between the changes in the IoT monitoring data of the target monitoring equipment and the changes in the recovery rate, and further combines the changes in other IoT monitoring data to realize the storage management of the IoT monitoring data of recycling equipment with relatively large changes under specific conditions, ensuring the reliability of storage management.

[0014] A further technical solution is that the recovery rate in different recycling processes is determined according to the tin recovery monitoring data in different recycling processes.

[0015] A further technical solution is that determining that the fluctuation of the recovery rate is within a preset range specifically includes:

[0016] Based on the recovery rates in different numbers of recycling processes, determine the average value of the recovery rates in different numbers of recycling processes, and use it as the reference recovery rate;

[0017] According to the deviation of the recovery rates in different numbers of recycling processes from the reference recovery rate, determine the fluctuating recycling times in different numbers of recycling processes;

[0018] Based on the proportion of the fluctuating recycling times in the number of recycling processes, determine whether the fluctuation of the recovery rate is within a preset range.

[0019] A further technical solution is that the fluctuating recycling times in the number of recycling processes are based on the number of recycling processes in which the deviation amount of the recovery rate from the reference recovery rate is not within a preset deviation amount range.

[0020] A further technical solution is that when the proportion of the fluctuating recycling times in the number of recycling processes is greater than the preset proportion of fluctuating recycling times, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0021] A further technical solution is that when the fluctuation of the recovery rate is not within the preset range, the Internet of Things monitoring data of all recycling devices are stored and processed.

[0022] A further technical solution is that the method for determining the storage and processing strategy of the Internet of Things monitoring data of the recycling devices is as follows:

[0023] Based on the change situation of the recovery rate in the recycling process within a preset time period, determine the deviation amount of the recovery rate at different times in the recycling process from the reference recovery rate, and use the deviation amount from the reference recovery rate to determine the recovery rate change times in these times;

[0024] According to the change situation of the Internet of Things monitoring data of different target monitoring devices, determine the deviation amount of the Internet of Things monitoring data of different target monitoring devices from the reference monitoring data, and use the deviation amount from the reference monitoring data to determine the data change times of different Internet of Things monitoring data;

[0025] Based on the coincidence situation of different recovery rate change times and the data change times of different Internet of Things monitoring data, determine the proportion of the number of Internet of Things monitoring data belonging to the data change times in different recovery rate change times, and use it as the monitoring data change coincidence coefficient of the recovery rate change times;

[0026] According to the average value of the monitoring data change coincidence coefficients of different recovery rate change times, and the change situation of the Internet of Things monitoring data of the recycling devices, determine the storage and processing strategy of the Internet of Things monitoring data of the recycling devices.

[0027] A further technical solution lies in that the reference recovery rate and the reference monitoring data are determined according to the average values of the recovery rates and the monitoring data for different numbers of recovery processes.

[0028] A further technical solution lies in that, based on the average value of the monitoring data change coincidence coefficients at different recovery rate change moments and the change situation of the Internet of Things monitoring data of the recovery device, a storage and processing strategy for the Internet of Things monitoring data of the recovery device is determined, specifically including:

[0029] When the average value of the monitoring data change coincidence coefficients at different recovery rate change moments is less than the preset coincidence coefficient threshold, all the Internet of Things monitoring data of the recovery devices within the preset time period are stored and processed;

[0030] When the average value of the monitoring data change coincidence coefficients at different recovery rate change moments is not less than the preset coincidence coefficient threshold, the storage and processing strategy for the Internet of Things monitoring data of the recovery device is determined based on the change situation of the Internet of Things monitoring data of the recovery device.

[0031] A further technical solution lies in that the storage and processing strategy for the Internet of Things monitoring data of the recovery device is determined based on the change situation of the Internet of Things monitoring data of the recovery device, specifically including:

[0032] Based on the change situation of the Internet of Things monitoring data of the recovery device, the number of moments when the deviation amount between the Internet of Things monitoring data and the reference monitoring data does not meet the requirements is determined, and the Internet of Things monitoring data with the number of moments greater than the preset number of moments is used as the changed device data of the recovery device;

[0033] When the proportion of the changed device data of the recovery device in the Internet of Things monitoring data of the recovery device is greater than the preset device number proportion threshold, all the Internet of Things monitoring data of the recovery device within the preset time period are stored and processed;

[0034] When the proportion of the changed device data of the recovery device in the Internet of Things monitoring data of the recovery device is not greater than the preset device number proportion threshold, the changed monitoring data of the recovery device within the preset time period are stored and processed.

[0035] Other features and advantages will be described in the subsequent description. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the description and the drawings.

[0036] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following preferred embodiments are specifically described below in conjunction with the accompanying drawings. Description of the Drawings

[0037] The above and other features and advantages of the present invention will become more apparent by describing in detail its exemplary embodiments with reference to the accompanying drawings;

[0038] Figure 1 is a flowchart of a method for processing resource recovery data of materials with low tin content;

[0039] Figure 2 is a flowchart for determining that the fluctuation of the recovery rate is within a preset range;

[0040] Figure 3 is a flowchart of a method for determining the change monitoring data of a recycling device;

[0041] Figure 4 is a flowchart of a method for determining a target monitoring device;

[0042] Figure 5 is a flowchart of a method for determining the storage processing strategy of the Internet of Things monitoring data of a recycling device. Detailed Embodiments

[0043] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this specification.

[0044] In this application, by using the change situation of the Internet of Things monitoring data of different recycling devices, a differentiated storage strategy is generated, thereby improving the utilization efficiency of the storage space. It not only avoids the waste of the storage space, but also reduces the difficulty of data analysis and processing for the subsequent targeted improvement of the recycling process.

[0045] As Figure 1 shown, this application provides a method for processing resource recovery data of materials with low tin content, specifically including:

[0046] S1 Obtain the recovery rate of the materials with low tin content in different recycling times. When it is determined that the fluctuation of the recovery rate meets the requirements in different recycling times, proceed to the next step;

[0047] Based on the recovery rates in different numbers of recycling processes, determine the average value of the recovery rates in different numbers of recycling processes and use it as the reference recovery rate. Consider the number of recycling processes where the deviation between the recovery rate and the reference recovery rate is not within the preset deviation range as the fluctuating recycling times. When the proportion of the fluctuating recycling times in the total number of recycling processes is greater than 0.65, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0048] S4 Divide the number of recycling processes into different recycling process groups according to the recovery rate, obtain the variation of the Internet of Things monitoring data of the recycling equipment in different recycling process groups at different numbers of recycling processes, and determine the variation monitoring data of the recycling equipment based on the variation;

[0049] Divide the number of recycling processes with the recovery rate within the same recovery rate range into the same recycling process group.

[0050] Consider the moment when the variation amount of the Internet of Things monitoring data between adjacent moments is not within the preset variation range as the variation moment of the Internet of Things monitoring data. Take the average value of the proportion of the variation moments at different numbers of recycling processes as the data variation coefficient of the Internet of Things monitoring data in different recycling process groups. Consider the group with a data variation coefficient greater than 0.3 as the data variation group. When the sum of the proportions of the numbers of recycling processes corresponding to different data variation groups is greater than 0.45, it is determined that the Internet of Things monitoring data is variation monitoring data.

[0051] S3 Obtain the component data of the variation monitoring data of the recycling equipment, and in combination with the variation correlation between different variation monitoring data at different moments, when it is determined that the recycling equipment does not belong to the target monitoring equipment, based on the recovery rate in the recycling process and the variation of the Internet of Things monitoring data of the target monitoring equipment, and in combination with the variation of the Internet of Things monitoring data of the recycling equipment, determine the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment.

[0052] Determine the proportion of the quantity of the variation monitoring data of the recycling equipment and use it as the proportion of the variation data quantity. Determine the ratio of the variation amounts between different variation monitoring data at different moments and use it as the variation amount ratio. Consider the variation monitoring data with the variation amount ratio greater than the preset variation amount threshold at different moments as the variation correlation monitoring data. When the ratio of the proportion of the variation data quantity in the recycling equipment to the proportion of the quantity of the variation correlation monitoring data is greater than 3.5, it is determined that the recycling equipment is the target monitoring equipment.

[0053] Furthermore, the recovery rates in different numbers of recycling processes are determined according to the tin recovery monitoring data in different numbers of recycling processes.

[0054] Specifically, such asFigure 2 As shown, it is determined that the fluctuation of the recovery rate is within the preset range, specifically including:

[0055] Based on the recovery rates in different recovery treatment times, determine the average value of the recovery rates in different recovery treatment times, and use it as the reference recovery rate;

[0056] According to the deviation between the recovery rates in different recovery treatment times and the reference recovery rate, determine the fluctuating recovery times in different recovery treatment times;

[0057] Based on the proportion of the fluctuating recovery times in the recovery treatment times, determine whether the fluctuation of the recovery rate is within the preset range.

[0058] Further, the fluctuating recovery times in the recovery treatment times are based on the recovery treatment times when the deviation amount between the recovery rate and the reference recovery rate is not within the preset deviation amount range.

[0059] It should be noted that when the proportion of the fluctuating recovery times in the recovery treatment times is greater than the preset proportion of fluctuating recovery times, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0060] It can be understood that when the fluctuation of the recovery rate is not within the preset range, the Internet of Things monitoring data of all recovery devices are stored and processed.

[0061] In another possible embodiment, determining that the fluctuation of the recovery rate is within the preset range specifically includes:

[0062] Based on the recovery rates in different recovery treatment times, determine the average value of the recovery rates in different recovery treatment times, and use it as the reference recovery rate;

[0063] According to the deviation between the recovery rates in different recovery treatment times and the reference recovery rate, determine the recovery rate deviation amounts in different recovery treatment times;

[0064] Based on the average value of the recovery rate deviation amounts in different recovery treatment times, determine whether the fluctuation of the recovery rate is within the preset range.

[0065] Further, when the average value of the recovery rate deviation amounts in different recovery treatment times is greater than the preset deviation amount threshold, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0066] Optionally, determining that the fluctuation of the recovery rate is within the preset range specifically includes:

[0067] S11 Based on the recovery rates in different numbers of recycling processes, determine the average value of the recovery rates in different numbers of recycling processes, and use it as the reference recovery rate. According to the deviation between the recovery rates in different numbers of recycling processes and the reference recovery rate, determine the recovery rate deviation amount in different numbers of recycling processes, and determine the basic deviation coefficient based on the recovery deviation amounts in different numbers of recycling processes;

[0068] S12 According to the deviation of the recovery rate between different numbers of recycling processes and other numbers of recycling processes, determine the recovery rate fluctuation coefficient for different numbers of recycling processes, and determine the fluctuating recycling process numbers in the recycling processes based on the recovery rate fluctuation coefficient;

[0069] S13 Based on the proportion of the fluctuating recycling process numbers, the recovery rate fluctuation coefficient, and the basic deviation coefficient, determine the recovery rate fluctuation amount of the recovery rate, and determine whether the fluctuation situation of the recovery rate is within the preset interval according to the recovery rate fluctuation amount.

[0070] Further, when the recovery rate fluctuation amount is greater than the preset fluctuation amount threshold, determine that the fluctuation situation of the recovery rate is not within the preset interval.

[0071] Optionally, the above step S11 includes the following content:

[0072] S111 Based on the recovery rates in different numbers of recycling processes, determine the average value of the recovery rates in different numbers of recycling processes, and use it as the reference recovery rate. According to the deviation between the recovery rates in different numbers of recycling processes and the reference recovery rate, determine the recovery rate deviation amount in different numbers of recycling processes. When there are recycling process numbers with recovery rate deviation amounts not meeting the requirements, then transfer to step S113; when there are no recycling process numbers with recovery rate deviation amounts not meeting the requirements, then transfer to step S112;

[0073] S113 When the recovery rate deviation amounts of different numbers of recycling processes are all within the preset deviation amount interval, then determine that the fluctuation situation of the recovery rate is within the preset interval. When there are recycling process numbers with recovery rate deviation amounts not within the preset deviation amount interval, transfer to step S114;

[0074] S113 Obtain the recycling process numbers with recovery rate deviation amounts not meeting the requirements. When the number of recycling process numbers with recovery rate deviation amounts not meeting the requirements is greater than the preset deviation recycling process number, then determine that the fluctuation situation of the recovery rate is not within the preset interval. When the number of recycling process numbers with recovery rate deviation amounts not meeting the requirements is not greater than the preset deviation recycling process number, transfer to step S114;

[0075] S114 determines the basic deviation coefficient based on the recovery deviation amounts in different numbers of recovery processes. When the basic deviation coefficient is less than the preset deviation coefficient threshold, it proceeds to step S12. When the basic deviation coefficient is not less than the preset deviation coefficient threshold, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0076] Optionally, the above step S12 includes the following content:

[0077] S121 determines the recovery rate fluctuation coefficients for different numbers of recovery processes based on the deviation of the recovery rate between different numbers of recovery processes and other numbers of recovery processes. When the recovery rate fluctuation coefficients for different numbers of recovery processes are all less than the preset fluctuation coefficient threshold, it is determined that the fluctuation of the recovery rate is within the preset range. When there are numbers of recovery processes with recovery rate fluctuation coefficients not less than the preset fluctuation coefficient threshold, it proceeds to step S112;

[0078] S122 obtains the average value of the recovery rate fluctuation coefficients for different numbers of recovery processes. When the average value of the recovery rate fluctuation coefficients for different numbers of recovery processes does not meet the requirements, it is determined that the fluctuation of the recovery rate is within the preset range. When the average value of the recovery rate fluctuation coefficients for different numbers of recovery processes meets the requirements, it proceeds to step S123;

[0079] S123 takes the numbers of recovery processes with recovery rate fluctuation coefficients not less than the preset fluctuation coefficient threshold as the fluctuating recovery process numbers. When the fluctuating recovery process numbers do not meet the requirements, it is determined that the fluctuation of the recovery rate is not within the preset range. When the fluctuating recovery process numbers meet the requirements, it proceeds to step S124;

[0080] S124 obtains the proportion of the number of the fluctuating recovery process numbers in the total number of recovery processes. When the proportion is greater than the preset proportion of the number of fluctuating times, it proceeds to step S125. When the proportion is not greater than the preset proportion of the number of fluctuating times, it proceeds to step S13;

[0081] S125 When the average value of the recovery rate fluctuation coefficients for different fluctuating recovery process numbers is within the preset fluctuation coefficient range, it is determined that the fluctuation of the recovery rate is not within the preset range. When the average value of the recovery rate fluctuation coefficients for different fluctuating recovery process numbers is not within the preset fluctuation coefficient range, it proceeds to step S13.

[0082] Specifically, dividing the numbers of recovery processes into different recovery process groups includes:

[0083] Dividing the numbers of recovery processes with recovery rates within the same recovery rate range into the same recovery process group.

[0084] It should be noted that, such as Figure 3As shown, the method for determining the change monitoring data of the recycling equipment is as follows:

[0085] Based on the change situation of the Internet of Things monitoring data of the recycling equipment in the recycling treatment group at different recycling treatment times, determine the change moments of the Internet of Things monitoring data at different recycling treatment times in the recycling treatment group;

[0086] Based on the average value of the proportions of the change moments at different recycling treatment times, determine the data change coefficient of the Internet of Things monitoring data in different recycling treatment groups;

[0087] Determine the data change groups in the recycling treatment group according to the data change coefficients in different recycling treatment groups, and based on the proportions of the recycling treatment times corresponding to different data change groups, determine whether the Internet of Things monitoring data is change monitoring data.

[0088] Further, the change moment is the moment when the change amount of the Internet of Things monitoring data between adjacent moments is not within the preset change range.

[0089] Specifically, the data change group is the recycling treatment group with a data change coefficient greater than the preset data change coefficient threshold.

[0090] It should be noted that when the sum of the proportions of the recycling treatment times corresponding to different data change groups is greater than the preset recycling times proportion threshold, it is determined that the Internet of Things monitoring data is change monitoring data.

[0091] It can be understood that the method for determining the change monitoring data of the recycling equipment is as follows:

[0092] Based on the change situation of the Internet of Things monitoring data of the recycling equipment in the recycling treatment group at different recycling treatment times, determine the change moments of the Internet of Things monitoring data at different recycling treatment times in the recycling treatment group;

[0093] Based on the average value of the proportions of the change moments at different recycling treatment times, determine the data change coefficient of the Internet of Things monitoring data in different recycling treatment groups;

[0094] Determine the average change coefficient according to the average value of the data change coefficients in different recycling treatment groups, and based on the average change coefficient, determine whether the Internet of Things monitoring data is change monitoring data.

[0095] Further, when the average change coefficient is greater than the set value of the change coefficient, it is determined that the Internet of Things monitoring data is change monitoring data.

[0096] Optionally, the method for determining the change monitoring data of the recycling equipment is as follows:

[0097] S21 determines the change moments of the Internet of Things monitoring data at different recycling and processing times of the recycling equipment in the recycling and processing group according to the change situation of the Internet of Things monitoring data at different recycling and processing times of the recycling equipment in the recycling and processing group, and determines the change amount of the Internet of Things monitoring data at different recycling and processing times according to the proportion of the change moments at different recycling and processing times and the change amount of the Internet of Things monitoring data between different change moments and adjacent moments;

[0098] S22 determines the data change coefficient in the recycling and processing group based on the change amount of the Internet of Things monitoring data at different recycling and processing times in the recycling and processing group;

[0099] S23 determines the weight coefficients of different recycling and processing groups according to the proportion of the recycling and processing times in different recycling and processing groups, and determines the data change evaluation amount of the Internet of Things monitoring data by combining the data change coefficients in different recycling and processing groups, and determines whether the Internet of Things monitoring data is variable monitoring data based on the data change evaluation amount.

[0100] Further, the data change evaluation amount of the Internet of Things monitoring data is determined according to the weight sum of the data change coefficients in different recycling and processing groups.

[0101] Optionally, when the data change evaluation amount is greater than the preset data change evaluation amount threshold, it is determined that the Internet of Things monitoring data is variable monitoring data.

[0102] Optionally, the above step S21 includes the following contents:

[0103] S211 determines that if there are no change moments in the Internet of Things monitoring data at different recycling and processing times in different recycling and processing groups according to the change situation of the Internet of Things monitoring data at different recycling and processing times of the recycling equipment in the recycling and processing group, it is determined that the Internet of Things monitoring data does not belong to variable monitoring data. When there are change moments in the Internet of Things monitoring data at different recycling and processing times in different recycling and processing groups, it proceeds to step S213;

[0104] S212 determines that when the proportion of the number of recycling and processing times with no change moments in different recycling and processing groups is greater than the preset proportion of the number of change moments, it proceeds to step S214. When the proportion of the number of recycling and processing times with the proportion of the number of change moments greater than the preset proportion of the number of change moments, it is used as the variable recycling and processing times and proceeds to step S213;

[0105] S213 When the number of variable recovery processes is greater than the preset variable process number threshold, it is determined that the IoT monitoring data belongs to variable monitoring data. When the number of variable recovery processes is not greater than the preset variable process number threshold, it proceeds to step S214;

[0106] S214 Based on the proportion of variable moments at different recovery process numbers and the variable amount of IoT monitoring data between different variable moments and adjacent moments, determine the IoT data variable amount of the IoT monitoring data at different recovery process numbers. When there is a recovery process number with an IoT data variable amount greater than the preset data variable amount threshold, it proceeds to step S215. When there is no recovery process number with an IoT data variable amount greater than the preset data variable amount threshold, it proceeds to step S22;

[0107] S215 When the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold does not meet the requirements, it is determined that the IoT monitoring data belongs to variable monitoring data. When the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold meets the requirements, it proceeds to step S22.

[0108] Optionally, the following content is included in the above step S22:

[0109] S221 Based on the IoT data variable amount of the IoT monitoring data at different recovery process numbers in the recovery process group, calculate the proportion of the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold. When the proportion of the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold in different recovery process groups is less than the preset proportion threshold, it proceeds to step S223. When there is a recovery process group with a proportion of the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold not less than the preset proportion threshold, it proceeds to step S222;

[0110] S222 When the number of recovery process groups with a proportion of the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold not less than the preset proportion threshold does not meet the requirements, it is determined that the IoT monitoring data belongs to variable monitoring data. When the number of recovery process groups with a proportion of the number of recovery process numbers with an IoT data variable amount greater than the preset data variable amount threshold not less than the preset proportion threshold meets the requirements, it proceeds to step S223;

[0111] S223 Based on the Internet of Things (IoT) monitoring data in the recycling processing group, determine the data change coefficient in the recycling processing group according to the change amount of the IoT data in different recycling processing times. When the data change coefficients in different recycling processing groups are all less than the preset coefficient threshold, it is determined that the IoT monitoring data does not belong to the change monitoring data. When there is a recycling processing group with a data change coefficient not less than the preset coefficient threshold, go to step S224;

[0112] S224 When the number of recycling processing groups with a data change coefficient not less than the preset coefficient threshold does not meet the requirements, it is determined that the IoT monitoring data belongs to the change monitoring data. When the number of recycling processing groups with a data change coefficient not less than the preset coefficient threshold meets the requirements, go to step S23.

[0113] Specifically, as Figure 4 shown, the method for determining the target monitoring device is as follows:

[0114] Based on the component data of the change monitoring data of the recycling device, determine the proportion of the quantity of the change monitoring data of the recycling device and use it as the proportion of the quantity of the change data;

[0115] Based on the change correlation situation between different change monitoring data at different times, determine the ratio of the change amounts of different change monitoring data at different times and use it as the change amount ratio. Determine the change correlation monitoring data in the change monitoring data according to the change amount ratio at different times;

[0116] According to the proportion of the quantity of the change data and the proportion of the quantity of the change correlation monitoring data in the recycling device, determine the device data change amount of the recycling device, and use the device data change amount to determine whether the recycling device is the target monitoring device.

[0117] Furthermore, the change correlation monitoring data is the change monitoring data whose change amount ratios at different times are all within the preset change amount ratio interval.

[0118] Specifically, the device data change amount of the recycling device is determined according to the ratio of the proportion of the quantity of the change data to the proportion of the quantity of the change correlation monitoring data.

[0119] It should be noted that when the device data change amount of the recycling device is greater than the preset device data change amount threshold, it is determined that the recycling device is the target monitoring device.

[0120] Furthermore, when the recycling device is the target monitoring device, all the IoT monitoring data of the recycling device is stored and processed.

[0121] In another possible embodiment, the method for determining the target monitoring device is as follows:

[0122] Using the constituent data of the change monitoring data of the recycling device, when it is determined that there is no change monitoring data in the recycling device, it is determined that the recycling device does not belong to the target monitoring device;

[0123] When there is change monitoring data in the recycling device:

[0124] Obtain the quantity proportion of the change monitoring data of the recycling device and use it as the change data quantity proportion. When the change data quantity proportion is greater than the preset change quantity proportion threshold, it is determined that the recycling device is the target monitoring device;

[0125] When the change data quantity proportion is not greater than the preset change quantity proportion threshold:

[0126] When the quantity of the change monitoring data in the recycling device is less than the preset monitoring data quantity threshold, it is determined that the recycling device does not belong to the target monitoring device;

[0127] When the quantity of the change monitoring data in the recycling device is not less than the preset monitoring data quantity threshold:

[0128] Based on the change correlation situation between different change monitoring data at different times, determine the ratio of the change amounts of different change monitoring data at different times and use it as the change amount ratio. Determine the change correlation coefficient between different change monitoring data based on the change amount ratio at different times. When the change correlation coefficients between different change monitoring data are all greater than the preset change correlation coefficient threshold, it is determined that the recycling device does not belong to the target monitoring device;

[0129] When there is change monitoring data in the recycling device whose change correlation coefficient is not greater than the preset change correlation coefficient threshold:

[0130] Take the change monitoring data whose change correlation coefficients with other change monitoring data are not greater than the preset change correlation coefficient threshold as independent change monitoring data. When the quantity proportion of the independent change monitoring data in the recycling device is greater than the preset independent monitoring data quantity proportion, it is determined that the recycling device belongs to the target monitoring device;

[0131] When the quantity proportion of the independent change monitoring data in the recycling device is greater than the preset independent monitoring data quantity proportion:

[0132] Obtain the average value of the change correlation coefficients between different change monitoring data. When the average value of the change correlation coefficients between different change monitoring data is less than the preset change coefficient threshold, it is determined that the recycling device is the target monitoring device;

[0133] When the average value of the variation correlation coefficients between different variation monitoring data is not less than a preset variation coefficient threshold:

[0134] Based on the proportion of the quantity of variation data in the recycling equipment and the average value of the variation correlation coefficients between different variation monitoring data, determine the variation amount of the equipment data of the recycling equipment, and use the variation amount of the equipment data to determine whether the recycling equipment is a target monitoring equipment.

[0135] Specifically, as Figure 5 shown, the method for determining the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment is:

[0136] Based on the variation of the recovery rate during the recycling process within a preset time period, determine the deviation amount between the recovery rates at different times in the recycling process and the reference recovery rate, and use the deviation amount from the reference recovery rate to determine the time of recovery rate variation in these times;

[0137] Based on the variation of the Internet of Things monitoring data of different target monitoring equipment, determine the deviation amount between the Internet of Things monitoring data of different target monitoring equipment and the reference monitoring data, and use the deviation amount from the reference monitoring data to determine the data variation time of different Internet of Things monitoring data;

[0138] Based on the coincidence of different recovery rate variation times and the data variation times of different Internet of Things monitoring data, determine the proportion of the quantity of Internet of Things monitoring data belonging to the data variation time among different recovery rate variation times, and use it as the monitoring data variation coincidence coefficient of the recovery rate variation time;

[0139] Based on the average value of the monitoring data variation coincidence coefficients of different recovery rate variation times and the variation of the Internet of Things monitoring data of the recycling equipment, determine the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment.

[0140] Furthermore, the reference recovery rate and the reference monitoring data are determined according to the average value of the recovery rates and the average value of the monitoring data for different numbers of recycling processes.

[0141] It should be further noted that determining the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment based on the average value of the monitoring data variation coincidence coefficients of different recovery rate variation times and the variation of the Internet of Things monitoring data of the recycling equipment specifically includes:

[0142] When the average value of the monitoring data variation coincidence coefficients of different recovery rate variation times is less than a preset coincidence coefficient threshold, then store and process all the Internet of Things monitoring data of the recycling equipment within the preset time period;

[0143] When the average value of the monitoring data change coincidence coefficients at different recovery rate change moments is not less than the preset coincidence coefficient threshold, the storage and processing strategy of the Internet of Things monitoring data of the recovery device is determined based on the change situation of the Internet of Things monitoring data of the recovery device.

[0144] Specifically, determining the storage and processing strategy of the Internet of Things monitoring data of the recovery device based on the change situation of the Internet of Things monitoring data of the recovery device specifically includes:

[0145] Based on the change situation of the Internet of Things monitoring data of the recovery device, determine the number of moments when the deviation amount between the Internet of Things monitoring data and the reference monitoring data does not meet the requirements, and use the Internet of Things monitoring data with the number of moments greater than the preset number of moments as the changed device data of the recovery device;

[0146] When the proportion of the changed device data of the recovery device in the quantity of the Internet of Things monitoring data of the recovery device is greater than the preset device quantity proportion threshold, then store and process all the Internet of Things monitoring data of the recovery device within the preset time period;

[0147] When the proportion of the changed device data of the recovery device in the quantity of the Internet of Things monitoring data of the recovery device is not greater than the preset device quantity proportion threshold, then store and process the changed monitoring data of the recovery device within the preset time period.

[0148] Furthermore, the method for determining the storage and processing strategy of the Internet of Things monitoring data of the recovery device is:

[0149] Based on the change situation of the recovery rate during the recovery process within the preset time period, determine the deviation amount between the recovery rates at different moments in the recovery process and the reference recovery rate, and when there is no recovery rate change moment in the moments, only store and process the Internet of Things monitoring data of the target monitoring device within the preset time period;

[0150] When there are recovery rate change moments:

[0151] When the proportion of the number of recovery rate change moments does not meet the requirements, then store and process all the Internet of Things monitoring data of the recovery device within the preset time period;

[0152] When the proportion of the number of recovery rate change moments meets the requirements:

[0153] According to the change situations of the Internet of Things monitoring data of different target monitoring devices, determine the deviation amounts between the Internet of Things monitoring data of different target monitoring devices and the reference monitoring data, and use the deviation amounts from the reference monitoring data to determine the data change moments of different Internet of Things monitoring data;

[0154] Based on the coincidence between different recovery rate change times and the data change times of different Internet of Things monitoring data, determine the proportion of the number of Internet of Things monitoring data belonging to the data change time among different recovery rate change times, and use it as the monitoring data change coincidence coefficient of the recovery rate change time;

[0155] Determine the storage and processing strategy of the Internet of Things monitoring data of the recovery device according to the average value of the monitoring data change coincidence coefficients of different recovery rate change times and the change situation of the Internet of Things monitoring data of the recovery device.

[0156] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0157] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0158] The above is only one or more embodiments of this specification and is not used to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A data processing method for resource recovery of materials with low tin content, characterized in that, Specifically include: Obtain the recovery rates of the materials with low tin content in different recycling and treatment times. When it is determined that the fluctuation of the recovery rates in different recycling and treatment times meets the requirements, proceed to the next step; Divide the recycling and treatment times into different recycling and treatment groups according to the recovery rates, obtain the changes in the Internet of Things monitoring data of the recycling equipment in different recycling and treatment times in different recycling and treatment groups, and determine the change monitoring data of the recycling equipment based on the changes; Obtain the component data of the change monitoring data of the recycling equipment, and in combination with the change correlation between different change monitoring data at different times, when it is determined that the recycling equipment does not belong to the target monitoring equipment, based on the recovery rate in the recycling and treatment process and the changes in the Internet of Things monitoring data of the target monitoring equipment, and in combination with the changes in the Internet of Things monitoring data of the recycling equipment, determine the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment; The method for determining the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment is: Based on the changes in the recovery rate in the recycling and treatment process within a preset time period, determine the deviation amount between the recovery rates at different times in the recycling and treatment process and the reference recovery rate, and use the deviation amount from the reference recovery rate to determine the recovery rate change time in these times; According to the changes in the Internet of Things monitoring data of different target monitoring equipment, determine the deviation amount between the Internet of Things monitoring data of different target monitoring equipment and the reference monitoring data, and use the deviation amount from the reference monitoring data to determine the data change time of different Internet of Things monitoring data; Based on the coincidence of different recovery rate change times and the data change times of different Internet of Things monitoring data, determine the proportion of the number of Internet of Things monitoring data belonging to the data change time among different recovery rate change times, and use it as the monitoring data change coincidence coefficient of the recovery rate change time; Determine the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment according to the average value of the monitoring data change coincidence coefficients of different recovery rate change times and the changes in the Internet of Things monitoring data of the recycling equipment.

2. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that, The recovery rates in different recycling and treatment times are determined according to the tin recovery monitoring data in different recycling and treatment times.

3. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that Determine that the fluctuation of the recovery rate is within a preset range, specifically including: Based on the recovery rates in different recycling and treatment times, determine the average value of the recovery rates in different recycling and treatment times, and use it as the reference recovery rate; According to the deviation of the recovery rates in different recycling and treatment times from the reference recovery rate, determine the fluctuating recovery times in different recycling and treatment times; Based on the proportion of the fluctuating recovery times in the recycling and treatment times, determine whether the fluctuation of the recovery rate is within the preset range.

4. The resource recovery data processing method for materials with low tin content according to claim 3, characterized in that, The fluctuating recovery times in the recycling and treatment times are based on the recycling and treatment times when the deviation amount between the recovery rate and the reference recovery rate is not within the preset deviation amount range.

5. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that When the fluctuation of the recovery rate is not within the preset range, then store and process all the Internet of Things monitoring data of the recycling equipment.

6. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that Divide the number of recycling processes into different recycling process groups, specifically including: Divide the number of recycling processes within the same recycling rate range into the same recycling process group.

7. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that, The reference recycling rate and reference monitoring data are determined according to the mean values of the recycling rates and monitoring data for different numbers of recycling processes.

8. The resource recovery data processing method for materials with low tin content according to claim 1, characterized in that Determine the storage and processing strategy for the Internet of Things monitoring data of the recycling equipment based on the average value of the monitoring data change coincidence coefficients at different recycling rate change times and the change situation of the Internet of Things monitoring data of the recycling equipment, specifically including: When the average value of the monitoring data change coincidence coefficients at different recycling rate change times is less than the preset coincidence coefficient threshold, store and process all the Internet of Things monitoring data of the recycling equipment within the preset time period; When the average value of the monitoring data change coincidence coefficients at different recycling rate change times is not less than the preset coincidence coefficient threshold, determine the storage and processing strategy for the Internet of Things monitoring data of the recycling equipment based on the change situation of the Internet of Things monitoring data of the recycling equipment.

9. The data processing method for resource recovery of materials with low tin content according to claim 8, wherein, Determine the storage and processing strategy for the Internet of Things monitoring data of the recycling equipment based on the change situation of the Internet of Things monitoring data of the recycling equipment, specifically including: Based on the change situation of the Internet of Things monitoring data of the recycling equipment, determine the number of times when the deviation between the Internet of Things monitoring data and the reference monitoring data does not meet the requirements, and use the Internet of Things monitoring data with the number of times greater than the preset number of times as the changed equipment data of the recycling equipment; When the proportion of the changed equipment data of the recycling equipment in the quantity of the Internet of Things monitoring data of the recycling equipment is greater than the preset equipment quantity proportion threshold, store and process all the Internet of Things monitoring data of the recycling equipment within the preset time period; When the proportion of the changed equipment data of the recycling equipment in the quantity of the Internet of Things monitoring data of the recycling equipment is not greater than the preset equipment quantity proportion threshold, store and process the changed monitoring data of the recycling equipment within the preset time period.

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