Resource recycling data processing method for low-tin-content material

Abstract

The invention provides a resource recovery data processing method for a low-tin-content material, and belongs to the technical field of data processing, and the method specifically comprises the following steps: determining that a recovery device does not belong to a target monitoring device according to composition data of change monitoring data of the recovery device and change association conditions of different change monitoring data at different moments; the storage processing strategy of the Internet of Things monitoring data of the recovery equipment is determined on the basis of the recovery rate in the recovery processing process and the change condition of the Internet of Things monitoring data of the target monitoring equipment in combination with the change condition of the Internet of Things monitoring data of the recovery equipment, and the utilization efficiency of the storage space of the production data is improved.

Description

Technical Field

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

[0002] Low-tin content materials include electronic waste containing tin alloys, electroplating wastewater, tinplate waste, etc. The secondary recycling system can greatly improve the secondary utilization efficiency of low-tin content materials. At the same time, in the recycling process, how to realize the analysis and processing of recycling data and improve the recycling rate has become a technical problem that needs to be solved urgently.

[0003] In the existing technical solutions, when analyzing and processing the recycling data, the Internet of Things monitoring equipment is often used to monitor and analyze the recycling data in real time, and the operating status of the recycling processing device is adjusted in a targeted manner. Specifically, the invention patent application CN202410710272.4 "Unmanned control system, method, storage medium, equipment and program for solid waste" and CN201611254309.9 "A remote monitoring device for waste recycling and refining" both provide similar technical solutions, but the above technical solutions have the following defects: When recycling materials with low tin content, vacuum smelting, electrolytic refining, solvent extraction, membrane separation and other methods are often used in combination for recycling. As a result, the amount of data involved in the recycling process, including the recycling equipment and the IoT monitoring data of the recycling equipment, is large. Therefore, how to carry out targeted data storage management, store and process the IoT monitoring data with reference value as much as possible on the basis of reducing the storage pressure of production data, and provide reference for subsequent process improvements, has become a technical problem that needs to be solved urgently.

[0004] In order to solve the above technical problems, the present application provides a data processing method for resource recovery of low-tin content materials. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: Specifically, the present application provides a method for processing data of resource recovery of low-tin content materials, which specifically includes: S1 obtains the recovery rate of the low-tin content material in different recycling treatment times, and when the fluctuation of the recovery rate is determined by the recovery rate in different recycling treatment times to meet the requirements, proceeds to the next step; S4 divides the recycling processing times into different recycling processing groups according to the recycling rate, obtains changes in IoT monitoring data of recycling equipment in different recycling processing groups at different recycling processing times, and determines change monitoring data of the recycling equipment based on the changes; 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 to determine that the recycling equipment does not belong to the target monitoring equipment. Based on the recovery rate in the recycling process and the change of the IoT monitoring data of the target monitoring equipment, the storage and processing strategy of the IoT monitoring data of the recycling equipment is determined in combination with the change of the IoT monitoring data of the recycling equipment.

[0006] The beneficial effects of the present invention are: Whether the recycling equipment belongs to the target monitoring equipment is determined based on the composition data of the recycling equipment's change monitoring data and the change correlation between different change monitoring data at different times, thereby realizing the screening of recycling equipment with a relatively large number of change monitoring data. At the same time, it also further realizes the screening of change monitoring data with certain correlation between changes, and then realizes the screening of target monitoring equipment with a higher probability of change, which also lays the foundation for generating differentiated storage management strategies according to the changes in the monitoring data of the recycling equipment.

[0007] The storage and processing strategy of the IoT monitoring data of the recycling equipment is determined 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. Not only the difference in the storage and processing requirements for the IoT monitoring data due to the changes in the recovery rate is taken into account, but also the difference in the storage requirements for the IoT monitoring data of other recycling equipment due to the correlation between the changes in the IoT monitoring data of the target monitoring equipment and the changes in the recovery rate is taken into account. In addition, combined with the changes in other IoT monitoring data, the storage management of the IoT monitoring data of the recycling equipment with more drastic changes is realized under specific conditions, thereby ensuring the reliability of the storage management.

[0008] A further technical solution is that the recovery rates in the different recycling treatment times are determined based on the recovery monitoring data of tin in the different recycling treatment times.

[0009] A further technical solution is to determine that the fluctuation of the recovery rate is within a preset range, specifically including: Based on the recovery rates in different recycling treatment times, determine the average value of the recovery rates in different recycling treatment times and use it as the reference recovery rate; Determining the fluctuating recovery times among different recovery treatment times according to the deviations between the recovery rates among different recovery treatment times and the reference recovery rate; Based on the proportion of the number of fluctuating recovery times in the number of recovery processing times, it is determined whether the fluctuation of the recovery rate is within a preset range.

[0010] A further technical solution is that the fluctuating recovery number in the recovery processing times is the recovery processing times in which the deviation between the recovery rate and the reference recovery rate is not within a preset deviation range.

[0011] A further technical solution is that, when the proportion of the fluctuating recovery times in the recovery processing times is greater than the preset proportion of the fluctuating recovery times, it is determined that the fluctuation of the recovery rate is not within a preset range.

[0012] A further technical solution is that when the fluctuation of the recovery rate is not within a preset range, the Internet of Things monitoring data of all recycling equipment are stored and processed.

[0013] A further technical solution is that the method for determining the storage and processing strategy of the IoT monitoring data of the recycling equipment is: Based on the change of the recovery rate in the recycling process within a preset period of time, the deviation of the recovery rate at different moments in the recycling process from the benchmark recovery rate is determined, and the recovery rate change moment at the moment is determined by using the deviation from the benchmark recovery rate; According to the changes in the IoT monitoring data of different target monitoring devices, the deviations between the IoT monitoring data of different target monitoring devices and the benchmark monitoring data are determined, and the data change moments of the different IoT monitoring data are determined using the deviations from the benchmark monitoring data; Based on the overlap between different recovery rate change moments and different IoT monitoring data change moments, determine the proportion of IoT monitoring data belonging to the data change moment at different recovery rate change moments, and use it as the monitoring data change overlap coefficient at the recovery rate change moment; The storage and processing strategy of the Internet of Things monitoring data of the recycling device is determined according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the Internet of Things monitoring data of the recycling device.

[0014] A further technical solution is that the benchmark recovery rate and benchmark monitoring data are determined according to the mean of the recovery rate and the mean of the monitoring data at different recycling treatment times.

[0015] A further technical solution is to determine the storage and processing strategy of the IoT monitoring data of the recycling device according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the IoT monitoring data of the recycling device, specifically including: When the average value of the overlap coefficients of the monitoring data changes at different recovery rate change moments is less than the preset overlap coefficient threshold, the IoT monitoring data of all the recycling equipment within the preset period are stored and processed; When the average value of the monitoring data change overlap coefficients at different recovery rate change moments is not less than the preset overlap coefficient threshold, the storage and processing strategy of the IoT monitoring data of the recycling device is determined based on the change of the IoT monitoring data of the recycling device.

[0016] A further technical solution is to determine the storage and processing strategy of the IoT monitoring data of the recycling equipment based on the change of the IoT monitoring data of the recycling equipment, which specifically includes: Based on the change of the IoT monitoring data of the recycling device, determine the number of moments when the deviation between the IoT monitoring data and the benchmark monitoring data does not meet the requirement, and use the IoT monitoring data with a number of moments greater than the preset number of moments as the changed device data of the recycling device; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is greater than the preset device quantity proportion threshold, all IoT monitoring data of the recycling device within the preset period are stored and processed; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is not greater than a preset device quantity proportion threshold, the changed monitoring data of the recycling device within the preset time period is stored and processed.

[0017] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings; Figure 1 The present invention is a flow chart of a data processing method for resource recovery of low-tin content materials; Figure 2 It is a flow chart to determine the fluctuation of recovery rate within the preset range; Figure 3 is a flow chart of a method for determining change monitoring data of a recycling device; Figure 4 is a flow chart of a method for determining a target monitoring device; Figure 5 It is a flow chart of a method for determining a storage and processing strategy for Internet of Things monitoring data of a recycling device. DETAILED DESCRIPTION

[0020] 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 in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0021] In this application, the changes in IoT monitoring data of different recycling equipment are used to generate differentiated storage strategies, thereby improving the utilization efficiency of storage space. This not only avoids the waste of storage space, but also facilitates the targeted improvement of the recycling process in the later stage, reducing the difficulty of data analysis and processing.

[0022] like Figure 1 As shown, the present application provides a data processing method for resource recovery of low-tin content materials, which specifically includes: S1 obtains the recovery rate of the low-tin content material in different recycling treatment times, and when the fluctuation of the recovery rate is determined by the recovery rate in different recycling treatment times to meet the requirements, proceeds to the next step; Based on the recovery rates in different recycling treatment times, the average value of the recovery rates in different recycling treatment times is determined and used as the reference recovery rate. The recycling treatment times in which the deviation between the recovery rate and the reference recovery rate is not within the preset deviation range are taken as the fluctuating recovery times. When the proportion of the fluctuating recovery times in the recycling treatment times is greater than 0.65, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0023] S4 divides the recycling processing times into different recycling processing groups according to the recycling rate, obtains changes in IoT monitoring data of recycling equipment in different recycling processing groups at different recycling processing times, and determines change monitoring data of the recycling equipment based on the changes; The recycling treatment times with the same recycling rate range are divided into the same recycling treatment group.

[0024] The moment when the change in the IoT monitoring data between adjacent moments is not within the preset change range is taken as the change moment of the IoT monitoring data, the average value of the proportions of the change moments at different recycling and processing times is taken as the data change coefficient of the IoT monitoring data in different recycling and processing groups, the group with a data change coefficient greater than 0.3 is taken as the data change group, and when the sum of the proportions of recycling and processing times corresponding to different data change groups is greater than 0.45, the IoT monitoring data is determined to be changed monitoring data.

[0025] 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 to determine that the recycling equipment does not belong to the target monitoring equipment. Based on the recovery rate in the recycling process and the change of the IoT monitoring data of the target monitoring equipment, the storage and processing strategy of the IoT monitoring data of the recycling equipment is determined in combination with the change of the IoT monitoring data of the recycling equipment.

[0026] Determine the proportion of the number of change monitoring data of the recycling equipment, and use it as the proportion of the number of change data; determine the ratio of the change amounts between different change monitoring data at different times, and use it as the change amount ratio; use the change monitoring data whose change amount ratios at different times are greater than the preset change amount threshold as the change-associated monitoring data; when the ratio of the proportion of the number of change data in the recycling equipment to the proportion of the number of change-associated monitoring data is greater than 3.5, the recycling equipment is determined to be the target monitoring equipment.

[0027] Furthermore, the recovery rates in the different recycling treatment times are determined based on the recovery monitoring data of tin in the different recycling treatment times.

[0028] Specifically, Figure 2 As shown, the fluctuation of recovery rate is determined to be within the preset range, including: Based on the recovery rates in different recycling treatment times, determine the average value of the recovery rates in different recycling treatment times and use it as the reference recovery rate; Determining the fluctuating recovery times among different recovery treatment times according to the deviations between the recovery rates among different recovery treatment times and the reference recovery rate; Based on the proportion of the number of fluctuating recovery times in the number of recovery processing times, it is determined whether the fluctuation of the recovery rate is within a preset range.

[0029] Furthermore, the fluctuating recycling times in the recycling processing times are recycling processing times in which the deviation between the recovery rate and the reference recovery rate is not within a preset deviation range.

[0030] It should be noted that when the proportion of the fluctuating recovery times in the recovery processing times is greater than the preset proportion of the fluctuating recovery times, it is determined that the fluctuation of the recovery rate is not within the preset range.

[0031] It is understandable that when the fluctuation of the recovery rate is not within the preset range, the IoT monitoring data of all the recovery equipment are stored and processed.

[0032] In another possible embodiment, determining that the fluctuation of the recovery rate is within a preset range specifically includes: Based on the recovery rates in different recycling treatment times, determine the average value of the recovery rates in different recycling treatment times and use it as the reference recovery rate; Determining the deviation of the recovery rate in different recycling treatment times according to the deviation of the recovery rate in different recycling treatment times from the reference recovery rate; Based on the average value of the recovery rate deviation in different recovery treatment times, it is determined whether the fluctuation of the recovery rate is within a preset range.

[0033] Furthermore, when the average value of the recovery rate deviation in different recovery processing times is greater than a preset deviation threshold, it is determined that the fluctuation of the recovery rate is not within a preset range.

[0034] Optionally, determining that the fluctuation of the recovery rate is within a preset range includes: S11 determines the average value of the recovery rates in different recycling treatment times based on the recovery rates in different recycling treatment times, and uses it as a reference recovery rate, determines the recovery rate deviation amount in different recycling treatment times according to the deviation between the recovery rates in different recycling treatment times and the reference recovery rate, and determines the basic deviation coefficient based on the recovery deviation amount in different recycling treatment times; S12 determines the recovery rate fluctuation coefficients of different recycling times according to the deviation of the recovery rates between different recycling times and other recycling times, and determines the fluctuating recycling times among the recycling times based on the recovery rate fluctuation coefficients; S13 determines the recovery rate fluctuation amount of the recovery rate based on the proportion of the number of fluctuation recovery treatment times, the recovery rate fluctuation coefficient, and the basic deviation coefficient, and determines whether the recovery rate fluctuation is within a preset range based on the recovery rate fluctuation amount.

[0035] Further, when the recovery rate fluctuation is greater than a preset fluctuation threshold, it is determined that the recovery rate fluctuation is not within a preset range.

[0036] Optionally, the above step S11 includes the following contents: S111 determines the average value of the recovery rates in different recycling treatment times based on the recovery rates in different recycling treatment times, and uses it as a reference recovery rate. According to the deviation between the recovery rates in different recycling treatment times and the reference recovery rate, the recovery rate deviation in different recycling treatment times is determined. When there is a recycling treatment number whose recovery rate deviation does not meet the requirement, the process proceeds to step S113. When there is no recycling treatment number whose recovery rate deviation does not meet the requirement, the process proceeds to step S112. S113: When the recovery rate deviations of different recovery processing times are all within the preset deviation range, it is determined that the fluctuation of the recovery rate is within the preset range. When there is a recovery processing time whose recovery rate deviation is not within the preset deviation range, the process proceeds to step S114; S113 obtains the number of recycling processes for which the recovery rate deviation does not meet the requirements. When the number of recycling processes for which the recovery rate deviation does not meet the requirements is greater than the preset deviation recycling process number, it is determined that the fluctuation of the recovery rate is not within the preset range. When the number of recycling processes for which the recovery rate deviation does not meet the requirements is not greater than the preset deviation recycling process number, the process proceeds to step S114. S114 determines the basic deviation coefficient based on the recovery deviation in different recovery processing times. When the basic deviation coefficient is less than the preset deviation coefficient threshold, proceed 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.

[0037] Optionally, the above step S12 includes the following contents: S121 determines the recovery rate fluctuation coefficients of different recycling processing times according to the deviation of the recovery rates between different recycling processing times and other recycling processing times. When the recovery rate fluctuation coefficients of different recycling processing times are all less than the preset fluctuation coefficient threshold, it is determined that the fluctuation of the recovery rate is within the preset interval. When there is a recycling processing time whose recovery rate fluctuation coefficient is not less than the preset fluctuation coefficient threshold, the process proceeds to step S112; S122: obtaining the average value of the recovery rate fluctuation coefficients of different recycling treatment times. When the average value of the recovery rate fluctuation coefficients of different recycling treatment times does not meet the requirement, determining that the fluctuation of the recovery rate is within a preset range. When the average value of the recovery rate fluctuation coefficients of different recycling treatment times meets the requirement, proceeding to step S123; S123: The number of recycling processes in which the recovery rate fluctuation coefficient is not less than the preset fluctuation coefficient threshold is taken as the number of fluctuation recycling processes. When the number of fluctuation recycling processes does not meet the requirement, it is determined that the fluctuation of the recovery rate is not within the preset range. When the number of fluctuation recycling processes meets the requirement, the process proceeds to step S124. S124 obtains the proportion of the number of fluctuation recovery processing times in the number of recovery processing times. When the proportion is greater than the preset proportion of fluctuation times, proceed to step S125. When the proportion is not greater than the preset proportion of fluctuation times, proceed to step S13. S125 When the average value of the recovery rate fluctuation coefficient of different fluctuating recovery times 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 coefficient of different fluctuating recovery times is not within the preset fluctuation coefficient range, proceed to step S13.

[0038] Specifically, the recycling times are divided into different recycling groups, including: The recycling treatment times with the same recycling rate range are divided into the same recycling treatment group.

[0039] It should be noted that if Figure 3 As shown, the method for determining the change monitoring data of the recycling equipment is: Determine the change time of the Internet of Things monitoring data at different recycling processing times in the recycling processing group based on the change of the Internet of Things monitoring data of the recycling equipment in the recycling processing group at different recycling processing times; Determine the data variation coefficient of the IoT monitoring data in different recycling processing groups based on the average value of the proportion of the variation time at different recycling processing times; The data change group in the recycling processing group is determined according to the data change coefficient in different recycling processing groups, and whether the Internet of Things monitoring data is change monitoring data is determined based on the proportion of recycling processing times corresponding to different data change groups.

[0040] Furthermore, the change moment is a moment when the change amount of the Internet of Things monitoring data between adjacent moments is not within a preset change range.

[0041] Specifically, the data change group is a recycling processing group whose data change coefficient is greater than a preset data change coefficient threshold.

[0042] It should be noted that when the sum of the proportions of the number of recycling processes corresponding to different data change groups is greater than a preset recycling number proportion threshold, the Internet of Things monitoring data is determined to be change monitoring data.

[0043] It can be understood that the method for determining the change monitoring data of the recycling equipment is: Determine the change time of the Internet of Things monitoring data at different recycling processing times in the recycling processing group based on the change of the Internet of Things monitoring data of the recycling equipment in the recycling processing group at different recycling processing times; Determine the data variation coefficient of the IoT monitoring data in different recycling processing groups based on the average value of the proportion of the variation time at different recycling processing times; The average coefficient of variation is determined according to the average values ​​of the coefficients of variation of data in different recycling processing groups, and whether the Internet of Things monitoring data is variable monitoring data is determined based on the average coefficient of variation.

[0044] Furthermore, when the average variation coefficient is greater than a variation coefficient setting value, the Internet of Things monitoring data is determined to be variation monitoring data.

[0045] Optionally, the method for determining the change monitoring data of the recycling equipment is: S21 determines the change time of the IoT monitoring data at different recycling processing times in the recycling processing group based on the change of the IoT monitoring data of the recycling equipment in the recycling processing group at different recycling processing times, and determines the IoT data change amount of the IoT monitoring data at different recycling processing times based on the proportion of the change time at different recycling processing times and the change amount of the IoT monitoring data between different change time and adjacent time; S22 determines the data variation coefficient in the recycling processing group based on the IoT data variation of the IoT monitoring data in different recycling processing times in the recycling processing group; S23 determines the weight coefficients of different recycling processing groups according to the proportion of the number of recycling processing times in different recycling processing groups, and determines the data change evaluation amount of the Internet of Things monitoring data in combination with the data change coefficients in the different recycling processing groups, and determines whether the Internet of Things monitoring data is change monitoring data based on the data change evaluation amount.

[0046] Furthermore, the data change assessment amount of the IoT monitoring data is determined based on the weighted sum of the data change coefficients in different recycling processing groups.

[0047] Optionally, when the data change assessment amount is greater than a preset data change assessment amount threshold, the Internet of Things monitoring data is determined to be change monitoring data.

[0048] Optionally, the above step S21 includes the following contents: S211 determines that the IoT monitoring data of the recycling equipment in the recycling processing group at different recycling processing times do not have any change time based on the change of the IoT monitoring data, and then determines that the IoT monitoring data does not belong to the change monitoring data. When the IoT monitoring data of the recycling equipment in the recycling processing group at different recycling processing times has a change time, the process goes to step S213; When it is determined in step S212 that there is no recycling processing number whose ratio of the number of change time is greater than the preset ratio of the number of change time in different recycling processing groups, the process proceeds to step S214; when there is a recycling processing number whose ratio of the number of change time is greater than the preset ratio of the number of change time, it is regarded as the recycling processing number of change, and the process proceeds to step S213; S213: When the number of change recovery processing times is greater than the preset change processing times threshold, it is determined that the IoT monitoring data belongs to change monitoring data; when the number of change recovery processing times is not greater than the preset change processing times threshold, the process proceeds to step S214; S214 determines the IoT data change amount of the IoT monitoring data in different recycling processing times based on the proportion of the change time at different recycling processing times and the change amount of the IoT monitoring data between different change times and adjacent times. When there is a recycling processing time with an IoT data change amount greater than a preset data change amount threshold, the process proceeds to step S215. When there is no recycling processing time with an IoT data change amount greater than the preset data change amount threshold, the process proceeds to step S22. S215 When the change in IoT data is greater than the preset data change threshold and the number of recycling processing times does not meet the requirements, it is determined that the IoT monitoring data belongs to change monitoring data; when the change in IoT data is greater than the preset data change threshold and the number of recycling processing times meets the requirements, it proceeds to step S22.

[0049] Optionally, the above step S22 includes the following contents: S221, based on the IoT data change amount of the IoT monitoring data in different recycling processing times in the recycling processing group, calculates the proportion of the number of recycling processing times whose IoT data volume change amount is greater than the preset data change amount threshold. When the proportion of the number of recycling processing times whose IoT data volume change amount is greater than the preset data change amount threshold in different recycling processing groups is less than the preset quantity proportion threshold, proceed to step S223. When there is a recycling processing group whose proportion of the number of recycling processing times whose IoT data volume change amount is greater than the preset data change amount threshold is not less than the preset quantity proportion threshold, proceed to step S222. S222: When the number of recycling processing times for which the change in the amount of IoT data is greater than the preset data change threshold and the number of recycling processing groups for which the proportion is not less than the preset number proportion threshold does not meet the requirement, it is determined that the IoT monitoring data belongs to the change monitoring data; when the number of recycling processing times for which the change in the amount of IoT data is greater than the preset data change threshold and the number of recycling processing groups for which the proportion is not less than the preset number proportion threshold meets the requirement, the process proceeds to step S223; S223: determining the data variation coefficient in the recycling processing group based on the IoT data variation amount of the IoT monitoring data in different recycling processing times in the recycling processing group; when the data variation coefficients in different recycling processing groups are all less than the preset coefficient threshold, determining that the IoT monitoring data does not belong to the variation monitoring data; when there is a recycling processing group whose data variation coefficient is not less than the preset coefficient threshold, proceeding to step S224; S224 When the number of recycling processing groups whose data variation coefficient is not less than the preset coefficient threshold does not meet the requirements, it is determined that the IoT monitoring data belongs to variable monitoring data; when the number of recycling processing groups whose data variation coefficient is not less than the preset coefficient threshold meets the requirements, it proceeds to step S23.

[0050] Specifically, Figure 4 As shown, the method for determining the target monitoring device is: Determine the quantity ratio of the change monitoring data of the recycling equipment based on the constituent data of the change monitoring data of the recycling equipment, and use it as the quantity ratio of the change data; Based on the change correlation between different change monitoring data at different times, determine the ratio of the change amounts between different change monitoring data at different times, and use it as the change amount ratio, and determine the change correlation monitoring data in the change monitoring data by the change amount ratio at different times; The equipment data change amount of the recycling equipment is determined according to the proportion of the amount of changed data in the recycling equipment and the proportion of the amount of change-associated monitoring data, and the equipment data change amount is used to determine whether the recycling equipment is a target monitoring equipment.

[0051] Furthermore, the change-associated monitoring data are change monitoring data whose change ratios at different moments are all within a preset change ratio range.

[0052] Specifically, the amount of change in the equipment data of the recycling equipment is determined according to the ratio of the proportion of the amount of the changed data to the proportion of the amount of the change-associated monitoring data.

[0053] It should be noted that when the device data change amount of the recycling device is greater than a preset device data change amount threshold, the recycling device is determined to be a target monitoring device.

[0054] Furthermore, when the recycling device is a target monitoring device, all IoT monitoring data of the recycling device are stored and processed.

[0055] In another possible embodiment, the method for determining the target monitoring device is: When it is determined that no change monitoring data exists in the recycling device based on the constituent data of the change monitoring data of the recycling device, it is determined that the recycling device does not belong to the target monitoring device; When there is change monitoring data in the recycling equipment: Obtaining a quantity ratio of the change monitoring data of the recycling device, and using it as a quantity ratio of change data, and when the quantity ratio of change data is greater than a preset quantity ratio threshold, determining that the recycling device is a target monitoring device; When the percentage of the changed data is not greater than the preset percentage threshold of the changed data: When the amount of changed monitoring data in the recycling device is less than a preset monitoring data amount threshold, it is determined that the recycling device does not belong to the target monitoring device; When the amount of change monitoring data in the recycling device is not less than the preset monitoring data amount threshold: Based on the change correlation between different change monitoring data at different times, determine the ratio of the change amount between different change monitoring data at different times, and use it as the change amount ratio, and determine the change correlation coefficient between different change monitoring data by 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 recovery equipment does not belong to the target monitoring equipment; When the recovery equipment has change monitoring data whose change correlation coefficient is not greater than the preset change correlation coefficient threshold: The change monitoring data whose change correlation coefficient with other change monitoring data is not greater than the preset change correlation coefficient threshold is used as independent change monitoring data, and when the proportion of the number of independent change monitoring data in the recycling equipment is greater than the preset proportion of the number of independent monitoring data, it is determined that the recycling equipment belongs to the target monitoring equipment; When the proportion of the number of independent change monitoring data in the recycling equipment is greater than the preset proportion of the number of independent monitoring data: Obtaining an average value of the change correlation coefficients between different change monitoring data, and when the average value of the change correlation coefficients between different change monitoring data is less than a preset change coefficient threshold, determining that the recovery device is a target monitoring device; When the average value of the change correlation coefficients between different change monitoring data is not less than the preset change coefficient threshold: The equipment data change amount of the recycling equipment is determined according to the proportion of the number of change data in the recycling equipment and the average value of the change correlation coefficient between different change monitoring data, and the equipment data change amount is used to determine whether the recycling equipment is a target monitoring equipment.

[0056] Specifically, Figure 5As shown, the method for determining the storage and processing strategy of the IoT monitoring data of the recycling equipment is: Based on the change of the recovery rate in the recycling process within a preset period of time, the deviation of the recovery rate at different moments in the recycling process from the benchmark recovery rate is determined, and the recovery rate change moment at the moment is determined by using the deviation from the benchmark recovery rate; According to the changes in the IoT monitoring data of different target monitoring devices, the deviations between the IoT monitoring data of different target monitoring devices and the benchmark monitoring data are determined, and the data change moments of the different IoT monitoring data are determined using the deviations from the benchmark monitoring data; Based on the overlap between different recovery rate change moments and different IoT monitoring data change moments, determine the proportion of IoT monitoring data belonging to the data change moment at different recovery rate change moments, and use it as the monitoring data change overlap coefficient at the recovery rate change moment; The storage and processing strategy of the Internet of Things monitoring data of the recycling device is determined according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the Internet of Things monitoring data of the recycling device.

[0057] Furthermore, the benchmark recovery rate and benchmark monitoring data are determined according to the mean of the recovery rate and the mean of the monitoring data at different recycling treatment times.

[0058] It should be further explained that the storage and processing strategy of the IoT monitoring data of the recycling device is determined according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the IoT monitoring data of the recycling device, which specifically includes: When the average value of the overlap coefficients of the monitoring data changes at different recovery rate change moments is less than the preset overlap coefficient threshold, the IoT monitoring data of all the recycling equipment within the preset period are stored and processed; When the average value of the monitoring data change overlap coefficients at different recovery rate change moments is not less than the preset overlap coefficient threshold, the storage and processing strategy of the IoT monitoring data of the recycling device is determined based on the change of the IoT monitoring data of the recycling device.

[0059] Specifically, the storage and processing strategy of the IoT monitoring data of the recycling equipment is determined based on the change of the IoT monitoring data of the recycling equipment, which specifically includes: Based on the change of the IoT monitoring data of the recycling device, determine the number of moments when the deviation between the IoT monitoring data and the benchmark monitoring data does not meet the requirement, and use the IoT monitoring data with a number of moments greater than the preset number of moments as the changed device data of the recycling device; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is greater than the preset device quantity proportion threshold, all IoT monitoring data of the recycling device within the preset period are stored and processed; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is not greater than a preset device quantity proportion threshold, the changed monitoring data of the recycling device within the preset time period is stored and processed.

[0060] Furthermore, the method for determining the storage and processing strategy of the IoT monitoring data of the recycling equipment is: Based on the change of the recovery rate in the recycling process within a preset period of time, the deviation of the recovery rate at different moments in the recycling process from the benchmark recovery rate is determined, and when there is no recovery rate change moment at the moment, only the IoT monitoring data of the target monitoring device within the preset period of time is stored and processed; When there is a moment of recovery rate change: When the proportion of the number of recycling equipment at the time of recycling rate change does not meet the requirement, all IoT monitoring data of the recycling equipment within the preset period are stored and processed; When the quantity ratio at the time of recovery rate change meets the requirements: According to the changes in the IoT monitoring data of different target monitoring devices, the deviations between the IoT monitoring data of different target monitoring devices and the benchmark monitoring data are determined, and the data change moments of the different IoT monitoring data are determined using the deviations from the benchmark monitoring data; Based on the overlap between different recovery rate change moments and different IoT monitoring data change moments, determine the proportion of IoT monitoring data belonging to the data change moment at different recovery rate change moments, and use it as the monitoring data change overlap coefficient at the recovery rate change moment; The storage and processing strategy of the Internet of Things monitoring data of the recycling device is determined according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the Internet of Things monitoring data of the recycling device.

[0061] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0062] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A data processing method for resource recovery of low-tin content materials, characterized in that: Specifically include: Obtaining the recovery rate of the low-tin content material in different recycling treatment times, and determining the recovery rate fluctuation by the recovery rate in different recycling treatment times when the recovery rate meets the requirements, proceeding to the next step; Dividing the recycling processing times into different recycling processing groups according to the recycling rate, obtaining changes in IoT monitoring data of recycling equipment in different recycling processing groups at different recycling processing times, and determining change monitoring data of the recycling equipment based on the changes; The constituent data of the change monitoring data of the recycling equipment is obtained, and combined 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, the storage and processing strategy of the Internet of Things monitoring data of the recycling equipment is determined based on the recovery rate in the recycling process and the change of the Internet of Things monitoring data of the target monitoring equipment, and combined with the change of the Internet of Things monitoring data of the recycling equipment.

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

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

4. The method for processing data of resource recovery of low-tin content materials according to claim 3, characterized in that: The fluctuating recovery times in the recovery processing times are based on the recovery processing times in which the deviation between the recovery rate and the reference recovery rate is not within a preset deviation range.

5. The method for processing data of resource recovery of low-tin content materials according to claim 1, characterized in that: When the fluctuation of the recovery rate is not within the preset range, the IoT monitoring data of all the recovery equipment are stored and processed.

6. The method for processing data of resource recovery of low-tin content materials according to claim 1, characterized in that: The recycling times are divided into different recycling groups, specifically including: The recycling treatment times with the same recycling rate range are divided into the same recycling treatment group.

7. The method for processing data of resource recovery of low-tin content materials according to claim 1, characterized in that: The method for determining the storage and processing strategy of the IoT monitoring data of the recycling equipment is: Based on the change of the recovery rate in the recycling process within a preset period of time, the deviation of the recovery rate at different moments in the recycling process from the benchmark recovery rate is determined, and the recovery rate change moment at the moment is determined by using the deviation from the benchmark recovery rate; According to the changes in the IoT monitoring data of different target monitoring devices, the deviations between the IoT monitoring data of different target monitoring devices and the benchmark monitoring data are determined, and the data change moments of the different IoT monitoring data are determined using the deviations from the benchmark monitoring data; Based on the overlap between different recovery rate change moments and different IoT monitoring data change moments, determine the proportion of IoT monitoring data belonging to the data change moment at different recovery rate change moments, and use it as the monitoring data change overlap coefficient at the recovery rate change moment; The storage and processing strategy of the Internet of Things monitoring data of the recycling device is determined according to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the Internet of Things monitoring data of the recycling device.

8. The method for processing data of resource recovery of low-tin content materials according to claim 7, characterized in that: The benchmark recovery rate and benchmark monitoring data are determined based on the mean of the recovery rate and the mean of the monitoring data at different recovery treatment times.

9. The method for processing data of resource recovery of low-tin content materials according to claim 7, characterized in that: According to the average value of the monitoring data change overlap coefficient at different recovery rate change moments and the change of the IoT monitoring data of the recycling equipment, the storage and processing strategy of the IoT monitoring data of the recycling equipment is determined, specifically including: When the average value of the overlap coefficients of the monitoring data changes at different recovery rate change moments is less than the preset overlap coefficient threshold, the IoT monitoring data of all the recycling equipment within the preset period are stored and processed; When the average value of the monitoring data change overlap coefficients at different recovery rate change moments is not less than the preset overlap coefficient threshold, the storage and processing strategy of the IoT monitoring data of the recycling device is determined based on the change of the IoT monitoring data of the recycling device.

10. The method for processing data of resource recovery of low-tin content materials according to claim 9, characterized in that: The storage and processing strategy of the IoT monitoring data of the recycling device is determined based on the change of the IoT monitoring data of the recycling device, specifically including: Based on the change of the IoT monitoring data of the recycling device, determine the number of moments when the deviation between the IoT monitoring data and the benchmark monitoring data does not meet the requirements, and use the IoT monitoring data with a number of moments greater than the preset number of moments as the changed device data of the recycling device; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is greater than the preset device quantity proportion threshold, all IoT monitoring data of the recycling device within the preset period are stored and processed; When the proportion of the changed device data of the recycling device in the number of IoT monitoring data of the recycling device is not greater than a preset device quantity proportion threshold, the changed monitoring data of the recycling device within the preset time period is stored and processed.

Images