A performance simulation analysis method and system for a platinum recovery device

Abstract

The present invention provides a performance simulation analysis method and system for a platinum recovery device, which belongs to the field of data processing technology, and specifically comprises: determining the recovery deviation under different recovery material samples by comparing the deviation between the simulation results of a matching simulation model under different control schemes and the recovery results of corresponding historical recovery processing times; when there is no recovery material sample whose recovery deviation does not meet the requirements, obtaining the recovery data and recovery deviation of different types of recovery material samples, and determining a reliable simulation model in combination with the matching coefficients of different matching simulation models, adjusting the control variables of different operation links, and outputting process optimization suggestions under different types of recovery material samples based on the deviation between different simulation processing results and the deviation of different control variables, thereby ensuring the efficiency of platinum recovery analysis and processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a performance simulation analysis method and system for a platinum recovery device. Background Art

[0002] Since platinum is an essential catalyst in hydrogen fuel cells and the primary driving force for the rapid development of hydrogen fuel vehicles, how to recycle platinum has become a technical problem that needs to be solved urgently.

[0003] When recovering platinum, it can be recovered by using barium oxalateplatinate as a catalyst, a chlorine-free platinum source and (fluoro)acetylacetone, or by using NOx mixed gas. However, no matter which recovery method is used, the chemical recovery process is more complicated and difficult to manage. Therefore, if the recovery performance of the platinum recovery device cannot be simulated and analyzed, it is impossible to accurately make targeted improvements to improve the recovery efficiency.

[0004] In view of the above technical problems, the present invention provides a performance simulation analysis method and system for a platinum recovery device. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, a performance simulation analysis method for a platinum recovery device is provided.

[0007] A performance simulation analysis method for a platinum recovery device specifically comprises:

[0008] S1 obtains sample capture data of a collector of a platinum recovery device under different types of recovered material samples, and determines a matching simulation model and a matching coefficient of the platinum recovery device based on deviations between the sample capture data and different preset models;

[0009] S2 combines the control variables of different platinum recovery operation links to obtain multiple comparison control schemes, and determines the recovery deviation under different recovery material samples by matching the simulation results of the simulation model under different comparison control schemes with the deviation of the recovery results of the corresponding historical recovery times;

[0010] S3, when there is no recycled material sample whose recycling process deviation does not meet the requirements, obtaining recycling data and recycling process deviation of different types of recycled material samples, and determining a reliable simulation model in combination with matching coefficients of different matching simulation models;

[0011] S4 adjusts the control variables of different operation links, uses the reliable simulation model to simulate and obtain multiple simulation processing results, and outputs process optimization suggestions for different types of recycled material samples based on the deviations between different simulation processing results and the deviations of different control variables.

[0012] The beneficial effects of the present invention are:

[0013] 1. The matching simulation model and matching coefficient of the platinum recovery device are determined by using the deviation between the sample capture data and different preset models, thereby realizing the screening of the preset model from the perspective of the sample capture data, avoiding the technical problem of low accuracy of the simulation results of the simulation model due to large deviations in the sample capture data, and laying the foundation for the output of further process optimization suggestions.

[0014] 2. Based on the deviations between different simulation processing results and the deviations of different control variables, process optimization suggestions are output for different types of recycled material samples. This not only takes into account the differences in recovery rates caused by differences in simulation processing results, but also further considers the differences in data credibility caused by the deviations between different simulation processing results and the deviations of different control variables, thereby achieving the output of process optimization suggestions from multiple angles.

[0015] A further technical solution is that the recycled material samples include refinery catalysts, nitric acid plant catalysts, automobile waste catalysts, platinum carbon waste catalysts, and platinum-containing waste electronic components.

[0016] A further technical solution is that the sample capture data includes the sample capture amount and the sample capture success rate.

[0017] A further technical solution is that the value range of the matching coefficient is between 0 and 1, wherein the higher the matching coefficient is, the higher the degree of matching between the preset model and the platinum recovery device is.

[0018] A further technical solution is that the platinum recovery operation includes physical capture, pretreatment, chemical dissolution, ammonium salt precipitation separation and purification.

[0019] A further technical solution is that the control variables include ball milling particle size, solvent quality and effective content, roasting time and roasting temperature, heating time and insulation time.

[0020] A further technical solution is that the method for generating the comparison control scheme is:

[0021] Determine the control adjustment range of the control variables of different platinum recovery operation links based on the control variables of different platinum recovery operation links, and generate multiple sub-schemes of different platinum recovery operation links by using the control adjustment range;

[0022] The comparison control scheme is obtained by combining sub-schemes of different platinum recovery operation links.

[0023] A further technical solution is that the method for determining the reliable simulation model is:

[0024] By performing sorting processing on different types of recycled material samples according to the recycling processing deviations of different types of recycled material samples, the matching simulation model is used to obtain sorting results under different types of recycled material samples, and the sorting results are used to determine the comprehensive sorting results of different matching simulation results;

[0025] The comprehensive matching coefficients of different matching simulation models are determined according to the comprehensive ranking results and matching coefficients of the matching simulation models, and the reliable simulation model among the matching simulation models is determined using the comprehensive matching coefficients.

[0026] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, the performance simulation analysis method of a platinum recovery device mentioned above is executed.

[0027] 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.

[0028] 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

[0029] 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;

[0030] Figure 1 It is a flow chart of a performance simulation analysis method of a platinum recovery device;

[0031] Figure 2 is a flow chart of a method for determining a matching simulation model for a platinum recovery device;

[0032] Figure 3 is a flow chart of a method for generating a comparison control plan;

[0033] Figure 4 is a flow chart of a method for determining recycling process bias for a recycled material sample;

[0034] Figure 5 is a flow chart of a method for determining a reliable simulation model;

[0035] Figure 6 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0036] 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.

[0037] During chemical recycling, the recycling process is relatively complex and difficult to manage. Therefore, if the recovery performance of the platinum recovery device cannot be simulated and analyzed, it will be impossible to accurately make targeted improvements and improve the recycling efficiency.

[0038] In response to the above technical problems, the present invention constructs a reliable simulation model, and outputs process optimization suggestions for different types of recycled material samples according to the deviations between the simulation processing results of the reliable simulation model and the deviations of different control variables. Specifically, the process optimization suggestions for different types of recycled material samples are determined through the corresponding results of the control variables under the optimal simulation processing results.

[0039] Matching coefficient: Determine the average value of the deviation between the capture success rate of different types of recycled material samples and the preset model, and use the average value of the deviation to determine the matching coefficient. Specifically, for example, if the deviation of the capture success rate of the sample under recycled material sample A is 1%, and the deviation of the capture success rate of the sample under recycled material sample A is 2%, then the matching coefficient is 1-(1%+2%) / 2=0.985.

[0040] The matching simulation model is a simulation model with a matching coefficient greater than 0.9.

[0041] The recycling process deviation is determined according to the deviation between the simulation results of the matching simulation model and the recycling process results of the corresponding historical recycling process times under different comparison control schemes. For example, the simulation results of the matching simulation model under the waste hard disk drive, waste catalyst, and waste capacitor are 90%, 92%, and 95% recycling success rates, respectively, while the recycling success rates in the historical recycling process are 70%, 90%, and 92%, respectively. The recycling process deviation is 20%, 2%, and 3%. Among them, the recycling process deviation of the waste hard disk drive is relatively large, which does not meet the requirements. Therefore, the matching simulation model cannot be used as a reliable simulation model.

[0042] A reliable simulation model is a matching simulation model with a smaller recycling process deviation and a larger matching coefficient. The recycling deviation of different matching simulation models can be determined by multiplying the recycling volume proportion of different recycled material samples by the recycling process deviation. The matching simulation model with the largest ratio of the matching coefficient to the recycling deviation is taken as the reliable simulation model.

[0043] Output of process optimization suggestions: Use a reliable simulation model to adjust the control variables of the operation link, and output process optimization suggestions for different types of recycled material samples based on the corresponding control variables under the simulation processing results with the highest recovery rate.

[0044] The simulation model is built using existing finite element simulation software, including but not limited to ABAQUS and COMSOL Multiphysics.

[0045] Example 1

[0046] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a performance simulation analysis method for a platinum recovery device is provided, which specifically includes:

[0047] S1 obtains sample capture data of a collector of a platinum recovery device under different types of recovered material samples, and determines a matching simulation model and a matching coefficient of the platinum recovery device based on deviations between the sample capture data and different preset models;

[0048] Furthermore, the recycled material samples include refinery catalysts, nitric acid plant catalysts, automobile waste catalysts, platinum carbon waste catalysts, and platinum-containing waste electronic components.

[0049] It should be noted that the sample capture data includes the sample capture amount and the sample capture success rate.

[0050] Specifically, it should be noted that Figure 2 As shown, the method for determining the matching simulation model of the platinum recovery device is:

[0051] Determine the deviation of sample capture success rates of different types of recycled material samples by using the deviation of the sample capture data from different preset models;

[0052] The matching coefficients of different preset models are determined by taking the average values ​​of the deviations of the sample capture success rates of different types of recycled material samples, and whether the preset model is a matching simulation model is determined based on the matching coefficients.

[0053] Furthermore, the value range of the matching coefficient is between 0 and 1, wherein the higher the matching coefficient is, the higher the degree of matching between the preset model and the platinum recovery device is.

[0054] In another embodiment, the method for determining the matching simulation model of the platinum recovery device is:

[0055] Determine the deviation of sample capture success rate of different types of recycled material samples by using the deviation of the sample capture data and different preset models, and determine the deviation of the recycled material sample by using the deviation;

[0056] The matching coefficients of different preset models are determined by the quantity ratio of the deviation recovery material samples, and whether the preset model is a matching simulation model is determined based on the matching coefficient.

[0057] It should be noted that the use of the deviation amount to determine the deviation recovery material sample specifically includes:

[0058] When the deviation amount of the sample capture success rate of the recycled material sample is not within a preset deviation range, the recycled material sample is determined to be a deviation recycled material sample.

[0059] In another embodiment, the method for determining the matching simulation model of the platinum recovery device is:

[0060] Determine the deviation of sample capture success rate of different types of recycled material samples by using the deviation between the sample capture data and different preset models, and judge whether there are recycled material samples whose deviation does not meet the requirements of the preset model. If yes, determine that the preset model does not belong to the matching simulation model. If not, proceed to the next step.

[0061] Determine the deviation recovery material sample by using the deviation amount, and judge whether the number of the deviation recovery material samples of the preset model meets the requirement, if so, determine that the preset model does not belong to the matching simulation model, if not, proceed to the next step;

[0062] Determine the capture deviation of different types of recycled material samples based on the sample capture success rates of different types of recycled material samples and different preset models and the deviation of sample capture, and judge whether there are recycled material samples whose capture deviation does not meet the requirements in the preset model. If so, determine that the preset model does not belong to the matching simulation model. If not, proceed to the next step.

[0063] Determine the sample capture deviation amount according to the capture deviation amount of different deviation recovery material samples and the number of deviation recovery material samples, and judge whether the sample capture deviation amount meets the requirements. If not, determine that the preset model does not belong to the matching simulation model. If not, proceed to the next step;

[0064] The capture deviations of different recycled material samples are obtained, and matching coefficients of different preset models are determined in combination with the sample capture deviations, and whether the preset model is a matching simulation model is determined based on the matching coefficients.

[0065] S2 combines the control variables of different platinum recovery operation links to obtain multiple comparison control schemes, and determines the recovery deviation under different recovery material samples by matching the simulation results of the simulation model under different comparison control schemes with the deviation of the recovery results of the corresponding historical recovery times;

[0066] It should be noted that the platinum recovery operation includes physical capture, pretreatment, chemical dissolution, ammonium salt precipitation separation and purification.

[0067] Furthermore, the control variables include ball milling particle size, solvent quality and effective content, roasting time and roasting temperature, heating time and insulation time.

[0068] It is understandable that if Figure 3 As shown, the method for generating the comparison control scheme is:

[0069] Determine the control adjustment range of the control variables of different platinum recovery operation links based on the control variables of different platinum recovery operation links, and generate multiple sub-schemes of different platinum recovery operation links by using the control adjustment range;

[0070] The comparison control scheme is obtained by combining sub-schemes of different platinum recovery operation links.

[0071] It should be noted that if Figure 4 As shown, the method for determining the recycling process deviation of the recycled material sample is:

[0072] Using the historical recycling processing times corresponding to different comparison control schemes as the matching recycling processing times, using the simulation results of the matching simulation models of the different comparison control schemes as the matching simulation results, and determining the deviation amount from the recycling processing results of different matching recycling processing times according to the deviation between the matching access results and the recycling processing results of different matching recycling processing times;

[0073] The deviation of the processing results under different comparison control schemes is determined by the deviation of the recycling processing results with different matching recycling processing times, and the recycling processing deviation of the recycled material sample is determined based on the deviation of the processing results under different comparison control schemes.

[0074] Furthermore, the recycling processing deviation of the recycled material sample has a value range between 0 and 1, wherein the larger the recycling processing deviation of the recycled material sample is, the larger the simulation result of the recycled material sample in the matching simulation model is.

[0075] It can be understood that when there are recycled material samples whose recycling process deviation does not meet the requirements, it is determined that the matching simulation model does not meet the requirements and does not belong to a reliable simulation model.

[0076] In another embodiment, the method for determining the recycling process deviation of the recycled material sample is:

[0077] Using the historical recycling processing times corresponding to different comparison control schemes as the matching recycling processing times, using the simulation results of the matching simulation models of the different comparison control schemes as the matching simulation results, and determining the deviation amounts of the recycling processing results with different matching recycling processing times under different comparison control schemes according to the deviations between the matching simulation results and the recycling processing results with different matching recycling processing times;

[0078] Determine whether the average values ​​of the deviations of the recycling results of different matching recycling times under different comparison control schemes meet the requirements, if so, proceed to the next step, if not, determine that the recycling deviation of the recycled material sample does not meet the requirements;

[0079] Using the deviation of the recycling results of different matching recycling times under different comparison simulation schemes, the matching recycling times are divided into deviation recycling times and result consistent recycling times, and it is determined whether the proportion of the number of recycling times with consistent results to the number of matching recycling times under different comparison simulation schemes meets the requirements. If so, proceed to the next step; if not, it is determined that the recycling deviation of the recycled material sample does not meet the requirements;

[0080] Determine the deviation of the processing results under different comparison control schemes by comparing the deviation of the recycling processing results with different matching recycling processing times, the number of deviation recycling processing times, and the proportion of the deviation recycling processing times, and judge whether there is a comparison control scheme whose processing result deviation does not meet the requirements. If not, proceed to the next step. If yes, determine that the recycling processing deviation of the recycled material sample does not meet the requirements.

[0081] The recovery process deviation of the recovery material sample is determined based on the process result deviation under different comparison control schemes.

[0082] S3, when there is no recycled material sample whose recycling process deviation does not meet the requirements, obtaining recycling data and recycling process deviation of different types of recycled material samples, and determining a reliable simulation model in combination with matching coefficients of different matching simulation models;

[0083] It should be noted that if Figure 5 As shown, the method for determining the reliable simulation model is:

[0084] Determining the historical recycling processing times of different types of recycled material samples based on the recycling data of different types of recycled material samples, and determining the basic weight values ​​of different types of recycled material samples based on the historical recycling processing times;

[0085] Determining the simulation result deviation of the matching simulation model through the basic weight values ​​of different types of recycled material samples and the recycling process deviations of different types of recycled material samples;

[0086] The comprehensive matching deviations of different matching simulation models are determined according to the simulation result deviations and matching coefficients of the matching simulation models, and the reliable simulation model among the matching simulation models is determined using the comprehensive matching deviations.

[0087] Further, using the comprehensive matching deviation to determine a reliable simulation model in the matching simulation model specifically includes:

[0088] The matching simulation model with the smallest comprehensive matching deviation is taken as the reliable simulation model.

[0089] It should also be noted that the method for determining the reliable simulation model is:

[0090] By performing sorting processing on different types of recycled material samples according to the recycling processing deviations of different types of recycled material samples, the matching simulation model is used to obtain sorting results under different types of recycled material samples, and the sorting results are used to determine the comprehensive sorting results of different matching simulation results;

[0091] The comprehensive matching coefficients of different matching simulation models are determined according to the comprehensive ranking results and matching coefficients of the matching simulation models, and the reliable simulation model among the matching simulation models is determined using the comprehensive matching coefficients.

[0092] It should also be noted that the method for determining the reliable simulation model is:

[0093] S31 sorts the matching simulation model on different types of recycled material samples according to the recycling processing deviations of different types of recycled material samples to obtain sorting results under different types of recycled material samples, and uses the sorting results to determine whether the order of the matching simulation model under different types of recycled material samples is within a preset interval, if so, proceed to step S34, if not, proceed to the next step;

[0094] S32: taking the types of the recycled material samples whose order is not within the preset interval as screening types, and judging whether the number of the screening types meets the requirement, if so, proceeding to the next step, if not, determining that the matching simulation model does not belong to a reliable simulation model;

[0095] S33 determines the historical recycling processing times of different types of recycled material samples based on the recycling data of different types of recycled material samples, and determines the basic weight values ​​of different types of recycled material samples based on the historical recycling processing times, determines the important recycled samples in the recycled material samples by using the basic weight values, and judges whether the matching simulation model has important recycled samples whose sequence is not within the preset interval. If not, proceeds to the next step. If so, determines that the matching simulation model does not belong to a reliable simulation model.

[0096] S34 determines the simulation result deviation of the matching simulation model according to the basic weight values ​​of different types of recycled material samples and the recycling processing deviations of different types of recycled material samples, and judges whether the simulation result deviation of the matching simulation model meets the requirements. If so, proceed to the next step; if not, determine that the matching simulation model does not belong to a reliable simulation model;

[0097] S35 determines the comprehensive matching coefficients of different matching simulation models according to the simulation result deviations and matching coefficients of the matching simulation models, and determines the reliable simulation model among the matching simulation models using the comprehensive matching coefficients.

[0098] S4 adjusts the control variables of different operation links, uses the reliable simulation model to simulate and obtain multiple simulation processing results, and outputs process optimization suggestions for different types of recycled material samples based on the deviations between different simulation processing results and the deviations of different control variables.

[0099] Specifically, the method for outputting the process optimization suggestion is:

[0100] Determining the recommended processing results in the simulation processing results according to the recovery processing rates corresponding to the simulation processing results, and determining the result deviation amounts between the recommended processing results according to the deviations between the recommended processing results;

[0101] Determine the control variable deviations between different recommended processing results in different platinum recovery operation links based on the deviations of the control variables between different recommended processing results in different platinum recovery operation links, and determine the control parameter deviations using the control variable deviations in different platinum recovery operation links;

[0102] Determine the data similarity between the recommended processing result and other recommended processing results by using the result deviation and the control parameter deviation, and determine the data credibility of different recommended processing results by using the data similarity with other recommended processing results;

[0103] The comprehensive priority value of the recommended processing result is determined based on the data credibility and the recovery processing rate of the recommended processing result, and the screening recommended processing result is determined using the comprehensive priority value, and the control variables corresponding to the screening recommended processing result are used as the output of the process optimization suggestion.

[0104] In another embodiment, the method of outputting the process optimization suggestion is:

[0105] Determining the recommended processing results in the simulation processing results according to the recovery processing rates corresponding to the simulation processing results, and determining the result deviation amounts between the recommended processing results according to the deviations between the recommended processing results;

[0106] Determine the control variable deviations between different recommended processing results in different platinum recovery operation links based on the deviations of the control variables between different recommended processing results in different platinum recovery operation links, and determine the control parameter deviations using the control variable deviations in different platinum recovery operation links;

[0107] Determine the data similarity between the recommended processing result and other recommended processing results by using the result deviation and the control parameter deviation, and judge whether the number of other recommended processing results whose data similarity does not meet the requirement meets the requirement, if so, proceed to the next step, if not, it is impossible to output the process optimization suggestion based on the recommended processing result;

[0108] Determine the data credibility of different recommended processing results by data similarity with other recommended processing results, and judge whether the data credibility of the recommended processing results meets the requirements. If so, proceed to the next step; if not, it is impossible to output the process optimization suggestion based on the recommended processing results;

[0109] The comprehensive priority value of the credible recommended processing result is determined based on the data credibility and recovery processing rate of the credible recommended processing result, and the screening recommended processing result is determined using the comprehensive priority value, and the control variables corresponding to the screening recommended processing result are used as the output of the process optimization suggestion.

[0110] Example 2

[0111] Second, as Figure 6 As shown, the present invention provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, the performance simulation analysis method of a platinum recovery device mentioned above is executed.

[0112] The performance simulation analysis method of the platinum recovery device mentioned above specifically includes:

[0113] Determine different types of index requirements for different recycling needs based on the recycling needs of waste liquid recycling treatment, determine the deviation amounts of different types of index requirements for different recycling needs based on the deviations of different types of index requirements for different recycling needs, determine the adjustment deviation amounts of different types of indicators for different recycling needs in combination with the difficulty of adjusting different types of indicators, determine the indicator adjustment deviation amounts between different recycling needs based on the adjustment deviation amounts of different types of indicators, classify different recycling needs into the same demand group based on the indicator adjustment deviation amounts, and determine the matching index requirements for different demand groups based on the indicator requirements of the recycling needs;

[0114] Obtain different types of index concentrations of waste liquid at different historical treatment times, and determine the matching treatment target waste liquid of the demand group in combination with the matching index requirements of the demand group;

[0115] Determine the associated treatment equipment by using the treatment method matching different types of indicators of the target waste liquid, and determine the reliability of the adjustment processing of different associated treatment equipment based on the historical adjustment data and adjustment processing difficulty of different associated treatment equipment;

[0116] Generate a basic adjustment process plan by using the adjustment and processing reliability of the matching treatment target waste liquid of the demand group and the associated treatment equipment of different types of indicators;

[0117] Determine the historical number of treatments corresponding to different indicator concentration deviation intervals for indicators of a specified type through the deviations of different historical treatment times and the indicator concentrations of the matching target waste liquid for treatment in different types, and determine the interval discreteness of different indicator concentration intervals based on the deviations of the indicator concentrations of the specified type between the historical treatment times corresponding to different indicator concentration deviation intervals and the deviations of the indicator concentrations of the matching target waste liquid for treatment in the specified type;

[0118] Determine the distribution dispersion of the specified type of indicator through the interval dispersion of different indicator concentration intervals, and determine the treatment quantity threshold of the associated treatment device of the specified type of indicator through the distribution dispersion;

[0119] Determine the screening governance device for the indicator of the specified type based on the governance quantity threshold of the associated governance device of the indicator of the specified type and the adjustment processing reliability of different associated governance devices;

[0120] The matching treatment target waste liquid of the demand group is treated in combination in screening and treatment equipment with different specified types of indicators, and the process optimization plan of the demand group is determined in combination with the basic adjustment process plan.

[0121] 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.

[0122] 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.

[0123] 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 performance simulation analysis method for a platinum recovery device, characterized in that: Specifically include: Obtaining sample capture data of a collector of a platinum recovery device under different types of recovered material samples, and determining a matching simulation model and a matching coefficient of the platinum recovery device based on deviations between the sample capture data and different preset models; Based on the combination of control variables of different platinum recovery operation links, multiple comparison control schemes are obtained, and the deviation of the recovery process under different recovery material samples is determined by matching the simulation results of the simulation model under different comparison control schemes with the recovery process results of the corresponding historical recovery process times; When there are no recycled material samples whose recycling treatment deviation does not meet the requirements, the recycling data and recycling treatment deviations of different types of recycled material samples are obtained, and a reliable simulation model is determined in combination with the matching coefficients of different matching simulation models; Adjust the control variables of different operation links, use the reliable simulation model to simulate and obtain multiple simulation results, and output process optimization suggestions for different types of recycled material samples based on the deviations between different simulation results and the deviations of different control variables. The recycled material samples include refinery catalysts, nitric acid plant catalysts, automobile waste catalysts, platinum carbon waste catalysts, and platinum-containing waste electronic components; The method for determining the matching simulation model of the platinum recovery device is: Determine the deviation of sample capture success rates of different types of recycled material samples by using the deviation of the sample capture data from different preset models; Determine the matching coefficients of different preset models by taking the average values ​​of the deviations of the sample capture success rates of different types of recycled material samples, and determine whether the preset model is a matching simulation model based on the matching coefficients; The method for generating the comparison control scheme is: Determine the control adjustment range of the control variables of different platinum recovery operation links based on the control variables of different platinum recovery operation links, and generate multiple sub-schemes of different platinum recovery operation links by using the control adjustment range; Combining the sub-schemes of different platinum recovery operation links to obtain the comparison control scheme; The method for determining the reliable simulation model is: Determining the historical recycling processing times of different types of recycled material samples based on the recycling data of different types of recycled material samples, and determining the basic weight values ​​of different types of recycled material samples based on the historical recycling processing times; Determining the simulation result deviation of the matching simulation model through the basic weight values ​​of different types of recycled material samples and the recycling process deviations of different types of recycled material samples; The comprehensive matching deviations of different matching simulation models are determined according to the simulation result deviations and matching coefficients of the matching simulation models, and the reliable simulation model among the matching simulation models is determined using the comprehensive matching deviations.

2. The performance simulation analysis method of the platinum recovery device according to claim 1, characterized in that: The sample capture data includes a sample capture amount and a sample capture efficiency.

3. The performance simulation analysis method of the platinum recovery device according to claim 1, characterized in that: The platinum recovery operation includes physical capture, pretreatment, chemical dissolution, ammonium salt precipitation separation and purification.

4. The performance simulation analysis method of the platinum recovery device according to claim 1, characterized in that: The control variables include ball milling particle size, solvent quality and effective content, roasting time and roasting temperature, heating time and insulation time.

5. The performance simulation analysis method of the platinum recovery device according to claim 1, characterized in that: When there are recycled material samples whose recycling process deviations do not meet the requirements, it is determined that the matching simulation model does not meet the requirements and is not a reliable simulation model.

6. A computer system comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the performance simulation analysis method of a platinum recovery device according to any one of claims 1 to 5 when running the computer program.

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