Method, device and equipment for comprehensive evaluation of catalyst properties and storage medium

Abstract

The application discloses a catalyst property comprehensive evaluation method, device, equipment and storage medium, and comprises the following steps: converting original data in excel file format corresponding to a catalyst to be tested into a first list; determining a sub-list in the first list as a first reference sub-list, and setting other sub-lists as first comparison sub-lists respectively; determining a reference maximum value and a comparison maximum value; calculating the ratio of the reference maximum value and each comparison maximum value respectively; and correcting each content data; generating a second list by data reorganization on each sub-list in the first list; forming multiple comparison groups by the second reference sub-list and each second comparison sub-list respectively, and generating a similarity value according to the comparison result of the corresponding difference value data between two sub-lists in the comparison group. The application makes the characterization of catalyst properties more comprehensive, and thus improves the guiding significance of catalytic characterization for actual production.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of catalyst analysis, in particular to a catalyst property comprehensive evaluation method, device, equipment and storage medium. BACKGROUND

[0002] Different reaction products hide complex chemical reaction mechanisms and nature, and only by deeply studying the internal connection between various chemical reaction products can the nature of chemical reactions be clearly understood.

[0003] The catalyst is one of the most critical links in chemical reactions, and studying its properties is of great significance to the development of the chemical industry.

[0004] The existing instrument can measure some properties of the catalyst, such as the pore structure, acid properties and metal content of the catalyst.

[0005] The inventors have found that the existing technology has at least the following defects in measuring the properties of the catalyst by using instruments:

[0006] In practical applications, even if two catalysts have the same pore structure, acid properties, metal content, and similar preparation methods, their reaction results can still differ greatly. Therefore, the existing technology of using instrument measurement results to characterize the properties of the catalyst is not comprehensive enough.

[0007] The information disclosed in this BACKGROUND section is only intended to increase an understanding of the general context in which the present application can be practiced. It is not admitted that this information constitutes prior art that is already known in the art. SUMMARY

[0008] The purpose of the present application is to describe the similarity of the change rules of different reaction products by digital evaluation, thereby increasing the characterization of catalyst properties.

[0009] The present application provides a catalyst property comprehensive evaluation method, comprising the steps of:

[0010] S11, converting the original data in excel file format corresponding to the catalyst to be measured into a first list; the first list includes a plurality of sublists, each of which corresponds to a reaction product; the elements of the sublists include the identification and content data of the reaction product; the content data is the content data corresponding to a plurality of preset working condition parameters of the reaction product;

[0011] S12, determining a sublist in the first list as a first reference sublist, and setting other sublists as first comparison sublists respectively;

[0012] S13, determining a maximum value in the content data in the first reference sub-list as a reference maximum value, and determining a maximum value in the content data in each of the first comparison sub-lists as a comparison maximum value, respectively;

[0013] S14, calculating a ratio of the reference maximum value to each comparison maximum value, respectively; and correcting the content data in each of the first comparison sub-lists according to each ratio;

[0014] S15, generating a second list by data reorganization on each of the sub-lists in the first list, the data reorganization comprising: calculating a difference between each content data and the next content data to generate corresponding difference data as an element of each sub-list in the second list; each sub-list in the second list comprising a second reference sub-list corresponding to the first reference sub-list, and a second comparison sub-list corresponding to each of the first comparison sub-lists, respectively;

[0015] S16, grouping each of the second reference sub-lists and each of the second comparison sub-lists two by two to form a plurality of comparison groups, and generating a similarity degree value for representing the similarity degree of the change rule of a reaction product as a reference to other reaction products according to the comparison result of the corresponding difference data between two sub-lists in the comparison group.

[0016] Preferably, in the present application, it further comprises:

[0017] In the first list, another sub-list is determined as a first reference sub-list again, and the other sub-lists are set as first comparison sub-lists, respectively.

[0018] Returning to step S13 to step S16 until all sub-lists are first reference sub-lists.

[0019] Preferably, in the present application, the working condition parameters include a catalytic temperature or a catalytic time.

[0020] Preferably, in the present application, the plurality of preset working condition parameters include:

[0021] The plurality of catalytic temperatures are arranged in a stepwise increasing manner, or the plurality of catalytic times are arranged in a stepwise increasing manner.

[0022] Preferably, in the present application, the generating a similarity degree value for representing the similarity degree of the change rule of a reaction product as a reference to other reaction products according to the comparison result of the corresponding difference data between two sub-lists in the comparison group comprises:

[0023] Calculating a difference between each difference data of the second reference sub-list and the corresponding difference data of the second comparison sub-list in the comparison group two by two, and generating a comparison result list with each calculation result as an element.

[0024] According to the comparison result list, each calculation result value is graded by a preset grading rule, and the corresponding similarity degree value is determined according to the grading result.

[0025] Preferably, in the present application, the comparison result list, each calculation result value is graded by a preset grading rule, and the corresponding similarity degree value is determined according to the grading result, including:

[0026] Set the upper limit value and the lower limit value of the first preset interval;

[0027] Each of the calculation results is graded, including: the calculation results less than the lower limit value in the comparison result list are determined as the first level, the calculation results between the lower limit value and the upper limit value are determined as the second level, and the calculation results greater than the upper limit value are determined as the third level;

[0028] According to the statistical result of the calculation results in each level, the similarity degree value is generated.

[0029] Preferably, in the present application, the comparison result list, each calculation result value is graded by a preset grading rule, and the corresponding similarity degree value is determined according to the grading result, including:

[0030] The ratio of each calculation result value to the content data in the corresponding second reference sub-list is calculated as an error ratio value;

[0031] An error ratio value list composed of each error ratio value is generated;

[0032] Set the upper limit value and the lower limit value of the second preset interval;

[0033] Each of the error ratio values is graded, including: the error ratio values less than the lower limit value in the error ratio value list are determined as the first level, the error ratio values between the lower limit value and the upper limit value are determined as the second level, and the error ratio values greater than the upper limit value are determined as the third level;

[0034] According to the statistical result of the error ratio values in each level, the similarity degree value is generated.

[0035] Preferably, in the present application, the statistical result of the error ratio values in each level is generated, including:

[0036] The levels of the error ratio values in the multiple sub-lists included in the error ratio value list are counted respectively;

[0037] The sub-lists are assigned values, including: defining a sub-list including error ratio values of the third level as a first level assignment; defining a sub-list not including error ratio values of the third level and including error ratio values of the second level more than 2 / 3 as a second level assignment; defining a sub-list not including error ratio values of the third level and including error ratio values of the second level between 1 / 3 and 2 / 3 as a third level assignment; defining a sub-list not including error ratio values of the third level and including error ratio values of the second level less than 1 / 3 as a fourth level assignment; and defining a sub-list including error ratio values of the first level as a fifth level assignment.

[0038] The sub-lists of the error ratio list are respectively pre-calculated, including: calculating the average of all error ratio values in a sub-list, multiplying the average by 100, adding the value corresponding to the sub-list assignment, subtracting the obtained value by 100, and obtaining the similarity value.

[0039] Preferably, in the present application, the content data in each of the first comparison sub-lists is respectively modified according to each of the ratios, including:

[0040] The modified content data is generated by multiplying the ratio by the content data in the first comparison sub-list.

[0041] In another aspect of the present application, a catalyst property comprehensive evaluation device is also provided, including:

[0042] A first list generation unit is configured to convert raw data in an excel file format corresponding to a catalyst to be tested into a first list; the first list includes a plurality of sub-lists, each of the sub-lists corresponding to a reaction product; elements of the sub-lists include an identifier of the reaction product and content data of the reaction product; the content data is content data of the reaction product corresponding to a plurality of preset working condition parameters;

[0043] A reference determination unit is configured to determine a sub-list in the first list as a first reference sub-list, and set other sub-lists as first comparison sub-lists respectively;

[0044] A maximum value determination unit is configured to determine a maximum value of the content data in the first reference sub-list as a reference maximum value, and determine maximum values of the content data in each of the first comparison sub-lists as comparison maximum values respectively;

[0045] A modification unit is configured to calculate ratios of the reference maximum value and each of the comparison maximum values respectively, and modify the content data in each of the first comparison sub-lists according to each of the ratios;

[0046] The second list generation unit is used to generate a second list by reorganizing data in each of the sublists of the first list. The data reorganization includes: calculating the difference between each content data and its next content data to generate corresponding difference data as elements of each sublist in the second list; each sublist in the second list includes a second reference sublist corresponding to the first reference sublist, and a second comparison sublist corresponding to each of the first comparison sublists.

[0047] The similarity calculation unit is used to pair the second reference sublist with each of the second comparison sublists to form multiple comparison groups, and generate a similarity value to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products based on the comparison results of the corresponding difference data between the two sublists in the comparison group.

[0048] In another aspect of this invention, a comprehensive evaluation device for catalyst properties is also provided, comprising:

[0049] Memory, used to store computer programs;

[0050] A processor is used to invoke and execute the computer program to implement the various steps of the comprehensive evaluation method for catalyst properties as described in any of the preceding claims.

[0051] In another aspect of the present invention, a storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the various steps of the comprehensive evaluation method for catalyst properties as described in any of the preceding claims.

[0052] The catalyst property comprehensive evaluation device includes a computer program stored on a medium. The computer program includes program instructions. When the program instructions are executed by the computer, the computer performs the methods described in the above aspects and achieves the same technical effect.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] In this invention, a list is generated based on the content of various reactants at different reaction temperatures or reaction times. Then, the content values ​​of various reactants are unified to the same order of magnitude. Next, for a reactant, the variation range of the reactant between adjacent operating conditions is characterized by calculating the data difference between adjacent elements in the list. In this way, by quantifying the similarity of the overall variation range between different reactants, a similarity value can be generated to characterize the similarity of the variation patterns of a reaction product used as a reference with other reaction products.

[0055] As can be seen from the above scheme, the present invention characterizes the catalyst from the quantitative perspective of the similarity of the content change trends of the catalyst among different reactants in the reaction process, so as to make the characterization of catalyst properties more comprehensive and thus improve the guiding significance of catalytic characterization for actual production.

[0056] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, and to make the above and other objects, technical features and advantages of the present invention easier to understand, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings. Attached Figure Description

[0057] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a flowchart illustrating the steps of the comprehensive evaluation method for catalyst properties described in this invention;

[0059] Figure 2 This is a schematic diagram of the catalyst property comprehensive evaluation device described in this invention;

[0060] Figure 3 This is a schematic diagram of the catalyst property comprehensive evaluation device described in this invention. Detailed Implementation

[0061] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments.

[0062] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0063] In this document, the terms "first," "second," etc., are used to distinguish two different elements or parts, and are not used to define specific positions or relative relationships. In other words, in some embodiments, the terms "first," "second," etc., can also be used interchangeably.

[0064] Example One

[0065] To enhance the methods for characterizing catalyst properties by describing the similarity of changes in different reaction products through digital evaluation, such as...Figure 1 As shown, this embodiment of the invention provides a method for comprehensive evaluation of catalyst properties, including the following steps:

[0066] S11. Convert the raw data in the Excel file format corresponding to the catalyst to be tested into a first list; the first list includes multiple sub-lists, each sub-list corresponding to a reaction product; the elements of the sub-lists include the identifier of the reaction product and its content data; the content data is the content data of the reaction product under multiple preset operating parameters;

[0067] In practical applications, the original data of the catalyst in the Excel file format can be formatted as shown in Table 1:

[0068] Table 1:

[0069]

[0070] Table 1, taking the catalytic reaction temperature as the preset operating parameter as an example, records the content (mg) of various reaction products at different catalytic reaction temperatures. In practical applications, the operating parameter can also be catalytic time;

[0071] Taking Table 1 as an example of valid original data, in one embodiment of the present invention, the style of the first list converted can specifically be:

[0072] First list = [['Benzene', 4.0, 2.0, 3.0, 4.0], ['Toluene', 40.0, 20.0, 30.0, 40.0], ['Alkanes', 400.0, 220.0, 300.0, 400.0], ['Alkenes', 400.0, 200.0, 300.0, 380.0], ['Cycloalkanes', 400.0, 220.0, 300.0, 410.0], ['Diolefins', 375.0, 205.0, 305.0, 380.0]];

[0073] The sublists included in the first list: ['Benzene', 4.0, 2.0, 3.0, 4.0], ['Toluene', 40.0, 20.0, 30.0, 40.0], ['Alkanes', 400.0, 220.0, 300.0, 400.0], ['Alkenes', 400.0, 200.0, 300.0, 380.0], ['Cycloalkanes', 400.0, 220.0, 300.0, 410.0], and ['Diolefins', 375.0, 205.0, 305.0, 380.0], correspond to the types of reaction products, respectively; each sublist includes the identifier of the reaction product and its content data at different catalytic reaction temperatures.

[0074] In this embodiment of the invention, the multiple preset operating parameters can be set in a step-by-step manner, such as setting multiple different temperature values ​​in equal increments, or setting multiple different catalytic reaction times in equal increments; the specific difference setting can be set by those skilled in the art according to actual needs, and no specific determination is made here.

[0075] S12. Determine a sublist as the first reference sublist in the first list, and set the other sublists as the first comparison sublists respectively;

[0076] The first list includes a corresponding number of sublists based on the number of types of reaction products; for example, Table 1 includes 6 sublists.

[0077] The sublist corresponding to the reaction product used as a reference in each reaction product is used as the first reference sublist, and then the other sublists are used as the first comparison sublist for comparison.

[0078] Taking the sublist ['Benzene', 4.0, 2.0, 3.0, 4.0] in the first list of the above example as the first reference sublist, the other sublists ['Toluene', 40.0, 20.0, 30.0, 40.0], ['Alkanes', 400.0, 220.0, 300.0, 400.0], ['Alkenes', 400.0, 200.0, 300.0, 380.0], ['Cycloalkanes', 400.0, 220.0, 300.0, 410.0], and ['Diolefins', 375.0, 205.0, 305.0, 380.0] are the respective first comparison sublists.

[0079] S13. Determine the maximum value of the content data in the first reference sublist as the reference maximum value, and determine the maximum value of the content data in each of the first comparison sublists as the comparison maximum value;

[0080] Referring to the example above, the maximum value (i.e., the reference maximum value) in the first reference sublist ['Benzene', 4.0, 2.0, 3.0, 4.0] is 4.0; the maximum values ​​(i.e., the comparison maximum values) in the other first comparison sublists are 40.0, 400.0, 400.0, 410.0 and 380.0 respectively.

[0081] S14. Calculate the ratio of the reference maximum value to each comparison maximum value; and correct the content data in each of the first comparison sublists according to each ratio.

[0082] Referring to the above examples, the ratios of the reference maximum value to each comparison maximum value are 0.1, 0.01, 0.01, 0.0097560975609756 and 0.0105263157894738, respectively.

[0083] The content data in each of the first comparison sub-lists are adjusted according to each ratio. Specifically, the content data in each of the first comparison sub-lists is multiplied by the corresponding ratio to make the content data in the first comparison sub-lists and the content data in the first reference sub-lists at the same level of quantity comparison (i.e., at the same level of reference).

[0084] In the above example, after content data correction, the content data of each first comparison sublist are as follows:

[0085] [4.0, 2.0, 3.0, 4.0];

[0086] [4.0, 2.2, 3.0, 4.0];

[0087] [4.0, 2.0, 3.0, 3.8];

[0088] [3.902439024390244, 2.1463414634146343, 2.926829268292683, 4.0];

[0089] [3.9473684210526314, 2.1578947368421053, 3.210526315789474, 4.0].

[0090] S15. A second list is generated by reorganizing the data in each of the sublists of the first list. The data reorganization includes: calculating the difference between each content data and its next content data to generate corresponding difference data as elements of each sublist in the second list; each sublist in the second list includes a second reference sublist corresponding to the first reference sublist, and a second comparison sublist corresponding to each of the first comparison sublists.

[0091] The change in the difference between the content data in the first reference sublist and the first comparison sublist represents the change in the content of reactants caused by the change in the value of the operating parameters. Therefore, in this embodiment of the invention, it is also necessary to calculate the change in the content value of each reactant with the change of operating parameters (such as the temperature of each catalytic reaction) by difference calculation.

[0092] The data in the first reference sublist is reorganized into a second reference sublist, including:

[0093] The first reference sublist is [4.0, 2.0, 3.0, 4.0]. After difference calculation, the corresponding second reference sublist is [2.0, 1.0, 1.0].

[0094] The data in the first comparison sublist is reorganized into a second comparison sublist, which includes:

[0095] The first comparison sublist is: [4.0, 2.0, 3.0, 4.0]; after difference calculation, the corresponding second comparison sublist is: [2.0, 1.0, 1.0].

[0096] The first comparison sublist is: [4.0, 2.2, 3.0, 4.0]; after difference calculation, the corresponding second comparison sublist is: [1.799999999999998, 0.7999999999999998, 1.0].

[0097] The first comparison sublist is: [4.0, 2.0, 3.0, 3.8]; after difference calculation, the corresponding second comparison sublist is: [2.0, 1.0, 0.799999999999998].

[0098] The first comparison sublist is: [3.902439024390244, 2.1463414634146343, 2.926829268292683, 4.0]; after difference calculation, the corresponding second comparison sublist is: [1.7560975609756095, 0.7804878048780486, 1.0731707317073171];

[0099] The first comparison sublist is: [3.9473684210526314, 2.1578947368421053, 3.210526315789474, 4.0]; after difference calculation, the corresponding second comparison sublist is: [1.789473684210526, 1.0526315789473686, 0.7894736842105261];

[0100] S16. Pair the second reference sublist with each of the second comparison sublists to form multiple comparison groups, and generate a similarity value to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products based on the comparison results of the corresponding difference data between the two sublists in the comparison group.

[0101] The second reference sublist [2.0, 1.0, 1.0] is paired with each of the second comparison sublists to form multiple comparison groups. Then, based on the comparison results of the corresponding difference data between the two sublists in the comparison group, a similarity value is generated to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products.

[0102] The specific methods for generating similarity values ​​based on the comparison results of the corresponding difference data between two sublists in a comparison group can include:

[0103] The difference between each difference data in the second reference sublist of the comparison group and the corresponding difference data in the second comparison sublist are calculated pairwise, and a comparison result list is generated with each calculation result as an element.

[0104] Based on the numerical values ​​of each calculation result in the comparison result list, the calculation results are classified according to a preset classification rule, and the corresponding similarity value is determined based on the classification result.

[0105] The second reference sublist [2.0, 1.0, 1.0] and the second comparison sublist [2.0, 2.0, 1.0] (corresponding to toluene) form a comparison group. After calculating the differences between each pair, the calculation result in list form is [0.0, 0.0, 0.0].

[0106] The second reference sublist [2.0, 1.0, 1.0] and the second comparison sublist [1.8, 0.8, 1.0] (corresponding to alkanes) form a comparison group. After calculating the differences between each pair, the calculation result in tabular form is [0.2, 0.2, 0.0].

[0107] The second reference sublist [2.0, 1.0, 1.0] and the second comparison sublist [2.0, 1.0, 0.8] (corresponding to the olefin) form a comparison group. After calculating the differences between each pair, the calculation result in tabular form is [0.0, 1.0, 0.2].

[0108] The second reference sublist [2.0, 1.0, 1.0] and the second comparison sublist (corresponding to cycloalkanes) [1.75609756097561, 0.780487804878049, 1.073170731707317] form a comparison group. After calculating the differences between each pair, the calculation result in tabular form is [0.24390243902439, 1.219512195121951, 0.073170731707317].

[0109] The second reference sublist [2.0, 1.0, 1.0] and the second comparison sublist [1.789473684210527, 1.052631578947369, 0.789473684210526] (corresponding to the diene) form a comparison group. After calculating the differences between each pair, the calculation results in tabular form are [0.210526315789473, 0.947368421052631, 0.210526315789474].

[0110] The above calculation results characterize the differences between the changes in the content of 'benzene' during the reaction process and the changes in the content of other reactants ('toluene', 'alkanes', 'olefins', 'cycloalkanes', and 'diolefins') during the reaction process, using the change in the content of 'benzene' as a reference. This can reflect whether the changing trends of different reactants are synchronized as the reaction process proceeds, and the degree of synchronization.

[0111] In practical applications, after statistically analyzing the above calculation results, the similarity value can be obtained by calculating the average or median of each statistical result.

[0112] Preferably, in this embodiment of the invention, after obtaining the above calculation results, the similarity value can also be obtained in the following manner;

[0113] S21. Calculate the differences between each difference data in the second reference sublist of the comparison group and the corresponding difference data in the second comparison sublist, and generate a comparison result list with each calculation result as an element.

[0114] S22. Based on the numerical values ​​of each calculation result in the comparison result list, classify the calculation results according to the preset classification rules, and determine the corresponding similarity value based on the classification results.

[0115] This step may specifically include:

[0116] S221. Set the upper and lower limits of the first preset interval;

[0117] The calculation results are classified into three levels: calculation results in the comparison result list that are less than the lower limit value are classified as the first level; calculation results that are between the lower limit value and the upper limit value are classified as the second level; and calculation results that are greater than the upper limit value are classified as the third level.

[0118] S222. Generate the similarity value based on the statistical results of the calculation results in each level.

[0119] This step may specifically include:

[0120] The ratio of each calculation result to the content data in the corresponding second reference sublist is calculated as the error ratio.

[0121] Generate a list of error ratios consisting of each of the aforementioned error ratios;

[0122] Set the upper and lower limits of the second preset interval;

[0123] The error ratios are classified into three levels: error ratios in the error ratio list that are less than the lower limit are classified as first level (good); error ratios that are between the lower limit and the upper limit are classified as second level (middle); and error ratios that are greater than the upper limit are classified as third level (poor).

[0124] Based on the statistical results of the error ratios at each level, the similarity value is generated, specifically as follows:

[0125] The levels of the error ratios in the multiple sub-lists included in the error ratio list are statistically analyzed separately.

[0126] The sublists are assigned values ​​as follows: a sublist containing error ratios of the third level is defined as a first-level assignment (the value can be set to 0); a sublist excluding error ratios of the third level but containing more than 2 / 3 error ratios of the second level is defined as a second-level assignment (the value can be set to 10); a sublist excluding error ratios of the third level but containing between 1 / 3 and 2 / 3 error ratios of the second level is defined as a third-level assignment (the value can be set to 20); a sublist excluding error ratios of the third level but containing less than 1 / 3 error ratios of the second level is defined as a fourth-level assignment (the value can be set to 30); and a sublist where all error ratios are of the first level is defined as a fifth-level assignment (the value can be set to 50).

[0127] Each sublist of the error ratio list is pre-calculated, including: calculating the average value of all error ratios in a sublist, multiplying the average value by 100 and subtracting the value corresponding to the sublist, and subtracting the value from the result to obtain the similarity value.

[0128] In one example, the above similarity value can be calculated using the following process:

[0129] The error ratios and their corresponding levels in the multiple sublists included in the error ratio list are calculated using formula (1): (Second comparison sublist - Second reference sublist) / Second reference sublist. Specifically:

[0130] Toluene: The second comparison sublist [2.0, 1.0, 1.0] and the second reference sublist [2.0, 1.0, 1.0] are used to calculate the third comparison sublist [0.0, 0.0, 0.0] and the corresponding levels ['good', 'good', 'good'] using formula (1);

[0131] Alkanes: The second comparison sublist [1.799999999999998, 0.799999999999998, 1.0] and the second reference sublist [2.0, 1.0, 1.0] are used to calculate the third comparison sublist [0.10000000000000009, 0.20000000000000018, 0.0] and the corresponding levels ['middle', 'middle', 'good'] using formula (1);

[0132] The second comparison sublist of olefins: [2.0, 1.0, 0.7999999999999998] and the second reference sublist [2.0, 1.0, 1.0] are used to calculate the third comparison sublist [0.0, 0.0, 0.20000000000000018] and the corresponding levels ['good', 'good', 'middle'] using formula (1);

[0133] Cycloalkanes: The second comparison sublist [1.7560975609756095,0.7804878048780486,1.0731707317073171] and the second reference sublist [2.0, 1.0, 1.0] are calculated using formula (1) to obtain the third comparison sublist [0.12195121951219523,0.21951219512195141,0.07317073170731714] and the corresponding levels ['middle', 'middle', 'good'];

[0134] Diene: The second comparison sublist [1.789473684210526, 1.0526315789473686, 0.7894736842105261] and the second reference sublist [2.0, 1.0, 1.0] are calculated using formula (1) to obtain the third comparison sublist [0.10526315789473695, 0.052631578947368585, 0.2105263157894739] and the corresponding levels ['middle', 'good', 'middle'].

[0135] Using the average calculation formula, calculate the average value of each element in the third comparison sublist, and determine its corresponding assignment. Specifically:

[0136] Toluene: Average value: 0.0, and first-level assignment: 0;

[0137] Alkanes: Average value: 0.100000000000000009, and second-level assignment: 10;

[0138] Alkenes: average value obtained: 0.06666666666666672, and second-order assignment: 10;

[0139] Cycloalkanes: average value: 0.13821138211382125, and second-order assignment: 20;

[0140] Diolefins: average value obtained: 0.12280701754385981, and third-order assignment: 10;

[0141] According to formula (2): 100 - average value * 100 - graded assignment, calculate the similarity value corresponding to each reactant, where:

[0142] Toluene: Similarity: 100;

[0143] Alkanes: Similarity: 80;

[0144] Olefins: Similarity: 73;

[0145] Cycloalkanes: Similarity: 76;

[0146] Diene: Similarity: 78.

[0147] In summary, in this embodiment of the invention, a list is generated based on the content of various reactants at different reaction temperatures or reaction times; then, the content values ​​of various reactants are unified to the same order of magnitude; next, for a reactant, the variation range of the reactant between adjacent operating conditions is characterized by calculating the data difference between adjacent elements in the list; thus, by quantifying the similarity of the overall variation range between different reactants, a similarity value can be generated to characterize the similarity of the variation patterns of a reaction product used as a reference with other reaction products.

[0148] As can be seen from the above scheme, the embodiments of the present invention characterize the catalyst from the quantitative perspective of the similarity of the content change trends of the catalyst among different reactants in the reaction process, so as to make the characterization of catalyst properties more comprehensive and thus improve the guiding significance of catalytic characterization for actual production.

[0149] Example 2

[0150] Corresponding to the method embodiments, another aspect of the present invention provides a comprehensive evaluation device for catalyst properties. Figure 2This diagram illustrates the structure of a catalyst property comprehensive evaluation device provided in an embodiment of the present invention. The catalyst property comprehensive evaluation device is... Figure 1 The device corresponding to the comprehensive evaluation method of catalyst properties described in the corresponding embodiment is implemented through a virtual device. Figure 1 In the corresponding embodiment of the catalyst property comprehensive evaluation method, the various virtual modules constituting the catalyst property comprehensive evaluation device can be executed by electronic devices, such as network devices, terminal devices, or servers. Specifically, the catalyst property comprehensive evaluation device in the embodiment of the present invention includes:

[0151] The first list generation unit 01 is used to convert the raw data in the Excel file format corresponding to the catalyst to be tested into a first list; the first list includes multiple sub-lists, each of which corresponds to a reaction product; the elements of the sub-lists include the identifier of the reaction product and its content data; the content data is the content data of the reaction product under multiple preset operating parameters;

[0152] The reference determination unit 02 is used to determine a sublist as the first reference sublist in the first list, and set the other sublists as the first comparison sublist respectively;

[0153] The maximum value determination unit 03 is used to determine the maximum value of the content data in the first reference sublist as the reference maximum value, and to determine the maximum value of the content data in each of the first comparison sublists as the comparison maximum value;

[0154] Correction unit 04 is used to calculate the ratio of the reference maximum value to each comparison maximum value; and correct the content data in each of the first comparison sublists according to each ratio.

[0155] The second list generation unit 05 is used to generate a second list by reorganizing the data in each of the sub-lists of the first list. The data reorganization includes: calculating the difference between each content data and its next content data to generate corresponding difference data as elements of each sub-list in the second list; each sub-list in the second list includes a second reference sub-list corresponding to the first reference sub-list, and a second comparison sub-list corresponding to each of the first comparison sub-lists.

[0156] The similarity calculation unit 06 is used to pair the second reference sublist with each of the second comparison sublists to form multiple comparison groups, and generate a similarity value to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products based on the comparison results of the corresponding difference data between the two sublists in the comparison group.

[0157] It should be noted that the specific implementation and technical effects of the catalyst property comprehensive evaluation device in the embodiments of the present invention can be referred to Figure 1 The corresponding comprehensive evaluation methods for catalyst properties will not be elaborated here.

[0158] Example 3

[0159] Corresponding to the method embodiments, this invention also provides a comprehensive evaluation device for catalyst properties, such as a terminal or server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these.

[0160] An example diagram of the hardware structure block diagram of the catalyst property comprehensive evaluation device provided in this application is shown below. Figure 3 As shown, it may include:

[0161] Processor 1, communication interface 2, memory 3, and communication bus 4;

[0162] The processor 1, communication interface 2, and memory 3 communicate with each other via communication bus 4.

[0163] Optionally, communication interface 2 can be an interface of a communication module, such as the interface of a GSM module;

[0164] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0165] Memory 3 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0166] Specifically, processor 1 is used to execute the computer program stored in memory 3 to perform the following steps:

[0167] S11. Convert the raw data in the Excel file format corresponding to the catalyst to be tested into a first list; the first list includes multiple sub-lists, each sub-list corresponding to a reaction product; the elements of the sub-lists include the identifier of the reaction product and its content data; the content data is the content data of the reaction product under multiple preset operating parameters;

[0168] S12. Determine a sublist as the first reference sublist in the first list, and set the other sublists as the first comparison sublists respectively;

[0169] S13. Determine the maximum value of the content data in the first reference sublist as the reference maximum value, and determine the maximum value of the content data in each of the first comparison sublists as the comparison maximum value;

[0170] S14. Calculate the ratio of the reference maximum value to each comparison maximum value; and correct the content data in each of the first comparison sublists according to each ratio.

[0171] S15. A second list is generated by reorganizing the data in each of the sublists of the first list. The data reorganization includes: calculating the difference between each content data and its next content data to generate corresponding difference data as elements of each sublist in the second list; each sublist in the second list includes a second reference sublist corresponding to the first reference sublist, and a second comparison sublist corresponding to each of the first comparison sublists.

[0172] S16. Pair the second reference sublist with each of the second comparison sublists to form multiple comparison groups, and generate a similarity value to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products based on the comparison results of the corresponding difference data between the two sublists in the comparison group.

[0173] The above-described products can perform the methods provided in the embodiments of the present invention, and possess the corresponding functional modules and beneficial effects of performing the methods. Technical details not described in detail in this embodiment can be found in the comprehensive evaluation method for catalyst properties provided in the embodiments of the present invention.

[0174] Example 4

[0175] In this embodiment of the invention, a storage medium is also provided, which can store a program suitable for execution by a processor, the program being used for:

[0176] S11. Convert the raw data in the Excel file format corresponding to the catalyst to be tested into a first list; the first list includes multiple sub-lists, each sub-list corresponding to a reaction product; the elements of the sub-lists include the identifier of the reaction product and its content data; the content data is the content data of the reaction product under multiple preset operating parameters;

[0177] S12. Determine a sublist as the first reference sublist in the first list, and set the other sublists as the first comparison sublists respectively;

[0178] S13. Determine the maximum value of the content data in the first reference sublist as the reference maximum value, and determine the maximum value of the content data in each of the first comparison sublists as the comparison maximum value;

[0179] S14. Calculate the ratio of the reference maximum value to each comparison maximum value; and correct the content data in each of the first comparison sublists according to each ratio.

[0180] S15. A second list is generated by reorganizing the data in each of the sublists of the first list. The data reorganization includes: calculating the difference between each content data and its next content data to generate corresponding difference data as elements of each sublist in the second list; each sublist in the second list includes a second reference sublist corresponding to the first reference sublist, and a second comparison sublist corresponding to each of the first comparison sublists.

[0181] S16. Pair the second reference sublist with each of the second comparison sublists to form multiple comparison groups, and generate a similarity value to characterize the similarity of the change patterns of a reaction product used as a reference with other reaction products based on the comparison results of the corresponding difference data between the two sublists in the comparison group.

[0182] Optionally, the refined and extended functions of the program can be found in the description above.

[0183] The above-described product can execute the methods provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in other embodiments of the present invention.

[0184] The above-described product can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in the method provided in the embodiments of the present invention.

[0185] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0186] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0187] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0188] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0189] It should be understood that in the embodiments of this application, the claims, various embodiments, and features can be combined with each other to solve the aforementioned technical problems.

[0190] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0191] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for comprehensive evaluation of catalyst properties, characterized by, The method comprises the steps of: S11, converting the original data in excel file format corresponding to the catalyst to be tested into a first list; the first list comprises a plurality of sublists, each of which corresponds to a reaction product; the elements of the sublists include the identification and content data of the reaction product; the content data is the content data corresponding to a plurality of preset working condition parameters of the reaction product; S12, determining a sublist in the first list as a first reference sublist, and setting other sublists as first comparison sublists respectively; S13, determining the maximum value of the content data in the first reference sublist as a reference maximum value, and respectively determining the maximum value of the content data in each first comparison sublist as a comparison maximum value; S14, calculating the ratio of the reference maximum value to each comparison maximum value respectively; and correcting the content data in each first comparison sublist according to each ratio respectively, including: multiplying the ratio by the content data in the first comparison sublist to generate the corrected content data; S15, generating a second list by data reorganization of each sublist in the first list, the data reorganization including: calculating the difference between each content data and the next content data to generate corresponding difference data as the elements of each sublist in the second list; each sublist in the second list includes a second reference sublist corresponding to the first reference sublist, and a second comparison sublist corresponding to each first comparison sublist respectively; S16, grouping the second reference sublists and the second comparison sublists two by two to form a plurality of comparison groups, and generating a similarity value representing the similarity of the change rule of a reaction product as a reference to other reaction products according to the comparison results of the difference data between the two sublists in the comparison group, including: calculating the difference between each difference data in the second reference sublist and the corresponding difference data in the second comparison sublist in the comparison group two by two, and generating a comparison result list with each calculation result as an element; grading the calculation results according to the numerical values of each calculation result in the comparison result list through a preset grading rule, and determining the corresponding similarity value according to the grading result.

2. The comprehensive evaluation method for catalyst properties according to claim 1, characterized in that, Further comprising: determining another sublist in the first list as a first reference sublist again, and setting other sublists as first comparison sublists respectively; returning to steps S13 to S16 until all sublists are first reference sublists.

3. The method for comprehensive evaluation of catalyst properties according to claim 1, characterized in that, The working condition parameters include the catalytic reaction temperature or the catalytic time.

4. The method for comprehensive evaluation of catalyst properties according to claim 3, characterized in that, The plurality of preset working condition parameters include: a plurality of catalytic temperatures arranged in a stepwise increasing manner, or a plurality of catalytic times arranged in a stepwise increasing manner.

5. The method for comprehensively evaluating catalyst properties according to claim 4, characterized by, The grading of the calculation results according to the numerical values of each calculation result in the comparison result list through a preset grading rule, and the determination of the corresponding similarity value according to the grading result, include: setting the upper limit and lower limit of the first preset interval; grading the calculation results according to the numerical values of the calculation results in the result list by using a preset grading rule, and determining the similarity degree value according to the grading result; generating the similarity degree value according to the statistical result of the calculation results in each grade.

6. The method for comprehensively evaluating catalyst properties according to claim 1, characterized by, grading the calculation results according to the numerical values of the calculation results in the result list by using a preset grading rule, and determining the similarity degree value according to the grading result; respectively calculating the ratio of each calculation result value to the content data in the corresponding second reference sub-list as an error ratio value; generating an error ratio value list composed of the error ratio values; setting an upper limit value and a lower limit value of a second preset interval; grading the error ratio values, including: determining the error ratio values in the error ratio value list that are less than the lower limit value as a first grade, determining the error ratio values that are between the lower limit value and the upper limit value as a second grade, and determining the error ratio values that are greater than the upper limit value as a third grade; generating the similarity degree value according to the statistical result of the error ratio values in each grade.

7. The catalyst property comprehensive evaluation method according to claim 6, characterized by, grading the calculation results according to the numerical values of the calculation results in the result list by using a preset grading rule, and determining the similarity degree value according to the grading result; respectively counting the grades of the error ratio values in the multiple sub-lists included in the error ratio value list; assigning each sub-list, including: defining a sub-list including error ratio values of the third grade as a first assignment; defining a sub-list not including error ratio values of the third grade and including error ratio values of the second grade in an amount of more than 2 / 3 as a second assignment; defining a sub-list not including error ratio values of the third grade and including error ratio values of the second grade in an amount between 1 / 3 and 2 / 3 as a third assignment; defining a sub-list not including error ratio values of the third grade and including error ratio values of the second grade in an amount less than 1 / 3 as a fourth assignment; and defining a sub-list including error ratio values of the first grade as a fifth assignment; respectively performing a preset calculation on each sub-list of the error ratio value list, including: calculating the average value of all error ratio values in a sub-list, multiplying the average value by 100 and adding the assignment corresponding to the sub-list, subtracting the obtained value by 100 to obtain the similarity degree value.

8. A catalyst property comprehensive evaluation device characterized by comprising: including: a first list generation unit configured to convert the original data in an excel file format corresponding to the catalyst under test into a first list; the first list includes multiple sub-lists, and each sub-list corresponds to a reaction product; the elements of the sub-list include the identification and content data of the reaction product; the content data is the content data corresponding to the reaction product under multiple preset working parameters; a reference determination unit configured to determine a sub-list in the first list as a first reference sub-list, and set other sub-lists as first comparison sub-lists; a maximum value determining unit configured to determine a maximum value of the content data in the first reference sub-list as a reference maximum value, and determine a maximum value of the content data in each of the first comparison sub-lists as a comparison maximum value; a correction unit configured to calculate a ratio of the reference maximum value to each comparison maximum value; and correct the content data in each of the first comparison sub-lists according to the ratio; a second list generating unit configured to generate a second list by data reorganization on each of the sub-lists in the first list, the data reorganization including: calculating a difference between each content data and its subsequent content data to generate corresponding difference data as an element of each sub-list in the second list; each sub-list in the second list including a second reference sub-list corresponding to the first reference sub-list, and a second comparison sub-list corresponding to each of the first comparison sub-lists respectively; a similarity value calculating unit configured to group each of the second reference sub-list and each of the second comparison sub-lists into a plurality of comparison groups, and generate a similarity degree value representing a similarity degree of a reaction product as a reference to other reaction products according to a comparison result of the corresponding difference data between two sub-lists in the comparison group.

9. A catalyst property comprehensive evaluation apparatus characterized by comprising: comprising: a memory configured to store a computer program; a processor configured to call and execute the computer program to implement the steps of the catalyst property comprehensive evaluation method according to any one of claims 1-7.

10. A storage medium, characterized by comprising a software program adapted to be executed by a processor to implement the steps of the catalyst property comprehensive evaluation method according to any one of claims 1-7.

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