Method and apparatus for processing winding data, electronic device, and storage medium

Abstract

This application provides a method, apparatus, electronic device, and storage medium for processing wound data, belonging to the field of battery technology. The method includes: acquiring target processing parameters, a target processing file, and a target analysis mode; performing parameter checks on the target processing parameters according to the target analysis mode to obtain a check result; acquiring target wound data based on the check result and the target processing file; and processing the target wound data according to the target analysis mode to obtain a processing result. This application embodiment improves the processing efficiency of wound data.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method and apparatus for processing wound data, an electronic device, and a storage medium. Background Technology

[0002] A winding machine is a machine used to wind items or materials. For example, in the battery manufacturing process, a winding machine can wind the positive and negative electrode materials, separators, etc., to obtain the battery product. During this process, the winding machine generates various data, which can be used to monitor and control the winding quality, winding yield, etc. In related technologies, the data generated by the winding machine is processed manually, but this method suffers from low efficiency. Therefore, how to provide a method for processing winding data to improve the efficiency of processing the data generated by the winding machine has become an urgent technical problem to be solved. Summary of the Invention

[0003] The main objective of this application is to provide a method and apparatus for processing winding data, an electronic device and a storage medium, which aim to improve the processing efficiency of data generated by the winding machine.

[0004] To achieve the above objectives, a first aspect of this application provides a method for processing wound data, the method comprising:

[0005] Obtain target processing parameters, target processing files, and target analysis modes;

[0006] The target processing parameters are checked according to the target analysis mode to obtain the check results;

[0007] Obtain target winding data based on the inspection results and the target processing file;

[0008] The target winding data is processed according to the target analysis mode to obtain the processing result.

[0009] In some embodiments, the target analysis mode includes a first mode, the target processing parameters include processing limits and a first data column name, and the inspection result includes a first result;

[0010] The step of checking the target processing parameters according to the target analysis mode and obtaining the check results includes:

[0011] If the target analysis mode is the first mode, the processing limits are sorted to obtain the target sorting result;

[0012] If the target sorting result is equal to the preset sorting result, the target processing file is checked for header matching based on the first data column name to obtain the first result.

[0013] In some embodiments, obtaining target winding data based on the inspection results and the target processing file includes:

[0014] If the first result indicates that the target processing file includes a table header that matches the first data column name, the first data column index is obtained from the target processing file based on the first data column name;

[0015] The target winding data is obtained based on the index of the first data column.

[0016] In some embodiments, the target winding data is processed according to the target analysis pattern to obtain a processing result, including:

[0017] If the target analysis mode is the first mode, the target winding data is compared with the processing limit to obtain a comparison result;

[0018] The superiority rate is calculated based on the comparison results to obtain the superiority rate value;

[0019] The target winding data is sorted to obtain the maximum winding data and the minimum winding data;

[0020] The target winding data is calculated based on the maximum winding data and the minimum winding data to obtain the standard deviation;

[0021] The process stability of the target winding data is calculated based on the standard deviation to obtain a stable value.

[0022] The processing result is obtained based on the goodness-of-performance value and the stability value.

[0023] In some embodiments, the target analysis mode includes a second mode, the target processing parameters include analysis keywords and a second data column name, and the inspection result includes a second result;

[0024] The step of checking the target processing parameters according to the target analysis mode and obtaining the check results includes:

[0025] If the target analysis mode is the second mode, the analysis keywords are subjected to compliance testing to obtain compliance results;

[0026] If the compliance result indicates that the analysis keywords are compliant, the target processing file is checked for header matching based on the second data column name to obtain the second result.

[0027] In some embodiments, the target winding data is processed according to the target analysis pattern to obtain a processing result, including:

[0028] If the target winding data does not match the preset qualified data, the target winding data is matched with the analysis keywords to obtain the matching result;

[0029] If the matching result indicates that the target winding data matches the analysis keyword, the first matching quantity is obtained;

[0030] If the matching result indicates that the target winding data does not match the analysis keywords, winding keywords are generated based on the target winding data;

[0031] The second matching quantity is obtained based on the winding keywords and the target winding data;

[0032] The processing result is obtained based on the first matching quantity, the second matching quantity, the analysis keyword, and the winding keyword.

[0033] In some embodiments, the method further includes:

[0034] Based on the processing results and the target winding data, image processing is performed to obtain a winding analysis diagram;

[0035] The winding analysis diagram is displayed according to the preset display template.

[0036] To achieve the above objectives, a second aspect of this application provides a processing apparatus for wound data, the apparatus comprising:

[0037] The target data acquisition module is used to acquire target processing parameters, target processing files, and target analysis modes;

[0038] The parameter checking module is used to check the target processing parameters according to the target analysis mode and obtain the check results.

[0039] A winding data acquisition module is used to acquire target winding data based on the inspection results and the target processing file;

[0040] The winding data processing module is used to process the target winding data according to the target analysis mode to obtain the processing result.

[0041] To achieve the above objectives, a third aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect.

[0042] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0043] The winding data processing method, apparatus, electronic device, and storage medium proposed in this application perform parameter checks on target processing parameters through a target analysis mode, and obtain the target winding data to be analyzed and processed through the corresponding check results and target processing file. The target winding data is then processed through the target analysis mode to obtain the corresponding processing results. Therefore, the winding data processing method provided in this application, after obtaining the target processing parameters, target processing file, and target analysis mode, achieves automatic processing of the target winding data through steps such as parameter checking, obtaining the target winding data, and processing the target winding data. Compared with the manual processing methods in related technologies, this improves the processing efficiency of winding data. Attached Figure Description

[0044] Figure 1 This is a flowchart of the winding data processing method provided in the embodiments of this application;

[0045] Figure 2 This is a schematic diagram of the interface corresponding to the Cpk analysis provided in the embodiments of this application;

[0046] Figure 3 yes Figure 1 The flowchart of step S102 in the document;

[0047] Figure 4 This is another schematic diagram of the interface corresponding to the Cpk analysis provided in the embodiments of this application;

[0048] Figure 5 yes Figure 1 The flowchart of step S103 in the process;

[0049] Figure 6 yes Figure 1 The flowchart of step S104 in the process;

[0050] Figure 7 yes Figure 1 A flowchart of another embodiment of step S102;

[0051] Figure 8 This is a schematic diagram of the interface corresponding to the Pareto analysis provided in the embodiments of this application;

[0052] Figure 9 yes Figure 1 A flowchart of another embodiment of step S104 in the process;

[0053] Figure 10This is a schematic diagram of the structure of the winding data processing device provided in the embodiments of this application;

[0054] Figure 11 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0058] A winding machine is a machine used to wind items or materials. In the battery manufacturing process, a winding machine can wind the positive and negative electrode materials, separators, etc., to obtain the battery product. During this process, the winding machine generates various data, which can be used to monitor and control the winding quality, winding yield, etc. In related technologies, the data generated by the winding machine is processed manually, but this method suffers from low efficiency.

[0059] Based on this, embodiments of this application provide a method and apparatus for processing wound data, an electronic device, and a storage medium, aiming to improve the processing efficiency of wound data.

[0060] The winding data processing method, apparatus, electronic device, and storage medium provided in this application are specifically described through the following embodiments. First, the winding data processing method in this application embodiment is described.

[0061] The winding data processing method provided in this application relates to the field of battery technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent 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 software can be an application implementing the winding data processing method, but is not limited to the above forms.

[0062] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0063] Figure 1 This is an optional flowchart of the winding data processing method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.

[0064] Step S101: Obtain target processing parameters, target processing file, and target analysis mode;

[0065] Step S102: Perform parameter checks on the target processing parameters according to the target analysis mode, and obtain the check results;

[0066] Step S103: Obtain target winding data based on the inspection results and target processing file;

[0067] Step S104: Process the target winding data according to the target analysis mode to obtain the processing result.

[0068] Steps S101 to S104, as shown in the embodiments of this application, involve checking the target processing parameters using a target analysis mode, and obtaining the target winding data to be analyzed and processed based on the corresponding check results and the target processing file. The target winding data is then processed using the target analysis mode to obtain the corresponding processing results. Therefore, the winding data processing method provided in this application embodiment, after obtaining the target processing parameters, target processing file, and target analysis mode, achieves automatic processing of the target winding data through steps such as parameter checking, obtaining the target winding data, and processing the target winding data. Compared to the manual processing methods in related technologies, this method improves the processing efficiency of winding data.

[0069] In step S101 of some embodiments, the target processing parameter refers to the parameter used to limit the processing of winding data. The winding data refers to the data generated by the winding machine during operation, such as the outer edge distance of the negative electrode tab, the outer edge distance of the positive electrode tab, etc. By analyzing and processing the winding data, fault location and optimization of the winding machine can be performed. The target processing file refers to the file used to store the winding data, and is usually in tabular form. The target analysis mode refers to the mode for analyzing and processing the winding data, such as Cpk analysis (Cpk analysis is a statistical method used to evaluate process capability, measuring the stability and consistency of a process to determine whether the process can meet specific specifications) or Pareto analysis (Pareto analysis is a quality management analysis method used to identify the main causes of nonconforming products or problems). When the embodiments of this application are applied to an application, the target processing parameters, target processing file, and target analysis mode can be obtained based on the user's input operations on the corresponding interface of the application. For example, as... Figure 2 As shown, the target analysis mode is obtained through the user's switching operation in the mode switching control 201, the target processing parameters are obtained through the user's operation in the parameter selection box 202 or parameter input box 203, and the target processing file is obtained through the user's operation in the "data table selection" control 204. It is understood that there can be one or more target processing files, and this embodiment does not specifically limit this. Furthermore, in the file selection box opened by the "data table selection" control 204, the displayed candidate processing files can be filtered, such as retaining only CSV and Excel format candidate processing files, and the candidate processing files are sorted according to their last generation time. The target processing file is determined by the user's touch operation on the candidate processing files. Depending on actual needs, the size of the target processing file can also be checked to determine whether the size of the target processing file matches the current processing capacity.

[0070] In step S102 of some embodiments, parameter checking refers to checking whether the target processing parameters meet the requirements of the corresponding target analysis mode and obtaining the corresponding check results.

[0071] In step S103 of some embodiments, if the inspection result indicates that the target processing parameters meet the requirements of the corresponding target analysis mode, target winding data is obtained from the target processing file.

[0072] In step S104 of some embodiments, different analysis modes employ different analysis strategies. The target winding data is processed according to the analysis strategy corresponding to the acquired target analysis mode to obtain the corresponding processing result. Based on this processing result, operations such as analyzing the performance of the winding machine, locating faults in the winding machine, and optimizing the winding machine can be performed.

[0073] It is understood that target analysis modes can include Cpk analysis and Pareto analysis. The following sections will explain these two analysis modes in detail, based on the examples described above.

[0074] The following explains the Cpk analysis.

[0075] Reference Figure 3 In some embodiments, Cpk analysis is used as the first mode, the target processing parameters include processing limits and first data column names, and the inspection results include a first result. Step S102 includes, but is not limited to, steps S301 to S302.

[0076] Step S301: If the target analysis mode is the first mode, sort the processing limits to obtain the target sorting result;

[0077] Step S302: If the target sorting result is equal to the preset sorting result, perform a header matching check on the target processing file according to the first data column name to obtain the first result.

[0078] In step S301 of some embodiments, if the target analysis mode is determined to be Cpk analysis according to the above method, the processing limits are sorted from largest to smallest or smallest to largest. The processing limits include the limit corresponding to the warning line and the limit corresponding to the control line. (Refer to...) Figure 2 The processing limits can be obtained by the user entering them into the parameter input box 203. The limits corresponding to the warning line include upper limit 1 and lower limit 1, and the limits corresponding to the control line include upper limit 2 and lower limit 2. The upper limit 1, lower limit 1, upper limit 2, and lower limit 2 are sorted to obtain the target sorting result.

[0079] In step S302 of some embodiments, the preset sorting result refers to a correctly set sorting result in advance. For example, the preset sorting result could be lower limit 2 < lower limit 1 < upper limit 1 < upper limit 2. The target sorting result is compared with the preset sorting result. If the target sorting result is equal to the preset sorting result, it indicates that the processing limit setting is correct. When the processing limit setting is correct, the first data column name is checked to determine whether there is data in the header data of the target processing file that matches the first data column name, thus obtaining the first result. (Refer to...) Figure 2 The first data column name can be obtained by the user typing it into parameter input box 203. (See reference...) Figure 4 The target processing file can be in tabular form. The first data column name can be "Outer Margin of Negative Electrode", "Outer Margin of Positive Electrode", or "Inner Margin of Negative Electrode". The header data of the target processing file can be the first row of data in the table. If the first row of data includes data matching the first data column name, the target processing file will have a header matching the first data column name, indicating that the target processing parameters meet the requirements of the corresponding target analysis mode. Otherwise, the target processing file will not have a header matching the first data column name, indicating that the target processing parameters do not meet the requirements of the corresponding target analysis mode.

[0080] The advantage of steps S301 to S302 is that, before processing the target winding data, the target processing parameters are checked to determine whether the target processing parameters are set correctly. This reduces the possibility of processing the target winding data based on incorrect target processing parameters, thereby improving the accuracy of the processing results.

[0081] In some embodiments, refer to Figure 2 The processing limits can be copied using the "Copy" control 207. For example, the processing limit corresponding to the "positive tab outer margin" can be copied to the processing limit parameter input box 208 corresponding to the "negative tab outer margin" using the "Copy" control 207, or the processing limit corresponding to the "positive tab outer margin" can be copied to the processing limit parameter input box 209 corresponding to the "negative tab inner margin" using the "Copy" control 207. Through the above operations, the setting speed of the processing limits can be improved.

[0082] Reference Figure 5 In some embodiments, step S103 includes, but is not limited to, steps S501 to S502.

[0083] Step S501: If the first result indicates that the target processing file includes a table header that matches the first data column name, obtain the index of the first data column from the target processing file according to the first data column name;

[0084] Step S502: Obtain the target winding data according to the index of the first data column.

[0085] In step S501 of some embodiments, if the first result indicates that the target processing file includes a table header matching the first data column name, the column index of the first data column name in the target processing file is obtained to obtain the first data column index. For example, refer to Figure 4 Taking the first data column name as "Negative Ear Outer Margin" as an example, the index of the first data column can be BB. It is understandable that when there are multiple first data column names, multiple first data column indexes can be obtained.

[0086] In step S502 of some embodiments, the corresponding data in the target processing file is located and obtained according to the first data column index to obtain the target wrapping data. For example, multiple first data column indices include index1, index2, ..., indexN. The corresponding data column in the target processing file is located according to the first data column index, the corresponding data is read, and the read data is buffered into the corresponding queues queue1, queue2, ..., queueN to obtain the target wrapping data. It can be understood that when the target processing file contains multiple rows of empty data, a step-out reading can be set. If the target processing file contains multiple tables, the next table can be automatically read after a step-out reading, until all tables have been read.

[0087] Reference Figure 6 In some embodiments, step S104 includes, but is not limited to, steps S601 to S606.

[0088] Step S601: If the target analysis mode is the first mode, compare the target winding data with the processing limit to obtain the comparison result;

[0089] Step S602: Calculate the excellence rate based on the comparison results to obtain the excellence rate value;

[0090] Step S603: Sort the target winding data to obtain the maximum winding data and the minimum winding data;

[0091] Step S604: Calculate the target winding data based on the maximum and minimum winding data to obtain the standard deviation;

[0092] Step S605: Calculate the process stability of the target winding data based on the standard deviation to obtain a stable value;

[0093] Step S606: Obtain the processing result based on the goodness value and the stability value.

[0094] In step S601 of some embodiments, when the target analysis mode is Cpk analysis, the target winding data is compared with the processing limit to obtain the corresponding comparison result. Specifically, the data in each queue quene1, quene2...queneN is compared with the processing limit in turn to perform a performance evaluation. For example, each data value in queue quene1 is compared with the upper limit 1, lower limit 1, upper limit 2, and lower limit 2, and the number of values ​​< lower limit 2 (SumL2), the number of values ​​< lower limit 2 < value < lower limit 1 (SumL1), the number of values ​​< lower limit 1 < value < upper limit 1 (SumOK), the number of values ​​< upper limit 1 < value < upper limit 2 (SumU1), and the number of values ​​> upper limit 2 (SumU2) are recorded. The numbers SumL2, SumL1, SumOK, SumU1, and SumU2 are used as the comparison results.

[0095] In step S602 of some embodiments, the superiority rate is calculated based on the comparison result and the following formula (1) to obtain the superiority rate value.

[0096] Excellence rate = SumOK / (SumL2+SumL1+SumOK+SumU1+SumU2)......Equation (1)

[0097] It is understandable that the warning rate can also be calculated based on the comparison results and the following formula (2), and the NG rate (i.e. non-conforming type rate) can be calculated based on the comparison results and the following formula (3).

[0098] Early warning rate = (SumL1 + SumU1) / (SumL2 + SumL1 + SumOK + SumU1 + SumU2) ... Equation (2)

[0099] NG rate=(SumL2+SumU2) / (SumL2+SumL1+SumOK+SumU1+SumU2)...Equation (3)

[0100] In step S603 of some embodiments, the maximum winding data refers to the data with the largest value in the target winding data, and the minimum winding data refers to the data with the smallest value in the target winding data. For example, taking queue quene1 as an example, the data in queue quene1 is processed according to the bubble sort method to obtain the maximum winding data and the minimum winding data. The maximum winding data and the minimum winding data are accumulated and the average value Avg is calculated. Each data in queue quene1 is calculated with the average value Avg using the following equations (4) and (5) to obtain the standard deviation stedv.

[0101]

[0102]

[0103] Here, quene1[i] represents the i-th data in queue quene1, and quene1.count represents the total number of data in queue quene1.

[0104] In step S605 of some embodiments, cpku is calculated based on the set standard value stdValue and the following formula (6), and cpk1 is calculated based on the standard value stdValue and the following formula (7). The values ​​of cpku and cpk1 are compared, and the smaller value is taken as the stable value of the process.

[0105] cpku=(stdValue+upSpec-Avg) / (3×stdev)...Equation (6)

[0106] cpk1=-(stdValue-downSpec-Avg) / (3×stdev)...Equation (7)

[0107] Wherein, upSpec represents the upper limit value (upper limit value 1 or upper limit value 2), and downSpec represents the lower limit value (lower limit value 1 or lower limit value 2).

[0108] Understandably, the process precision cp can be calculated based on the standard deviation stedv and the following equation (8).

[0109] cp=(upSpec1+downSpece1) / (6×stdev)...Equation (8)

[0110] Where upSpec represents the upper limit value of 1, and downSpec represents the lower limit value of 1.

[0111] In step S606 of some embodiments, the excellence rate value and the stability value are used as the processing results. For example... Figure 2 As shown, the processing results can be displayed in the results statistics box 205. It is understood that the data calculated above, such as the warning rate and NG rate, can also be displayed in the results statistics box 205.

[0112] In some embodiments, the processing results can also be visualized, i.e., image processing is performed based on the processing results and the target winding data to obtain a winding analysis graph as shown in the result statistics box 205. Specifically, taking queue quene1 as an example, the range [lower limit 2, upper limit 2] is divided into 40 intervals, and the proportion of data in queue quene1 belonging to each interval is determined. The 40 intervals are used as the horizontal axis of the winding analysis graph, and the proportion belonging to each interval is used as the vertical axis of the winding analysis graph. It is understood that in this embodiment, the content of the horizontal axis and the content of the vertical axis are used as a preset display template. According to the actual analysis needs, the content of the horizontal axis and the content of the vertical axis can be adjusted, i.e., the preset display template can be adjusted to meet personalized analysis needs. This embodiment does not specifically limit this.

[0113] In some embodiments, after each visualization process is completed, it is possible to perform operations such as... Figure 2 Take a screenshot of the interface shown and save the image to the corresponding file path, such as the "Data Analysis Results" file path. Alternatively, you can... Figure 2 In the file selection box 206, select the file path for "Data Analysis Results" to view the corresponding visualization screenshots of historical processing results.

[0114] The following explains Pareto analysis.

[0115] Reference Figure 7 In other embodiments, Pareto analysis is used as the second mode, the target processing parameters include analysis keywords and second data column names, the inspection results include a second result, and step S102 includes, but is not limited to, steps S701 to S702.

[0116] Step S701: If the target analysis mode is the second mode, perform compliance checks on the analysis keywords to obtain compliance results;

[0117] Step S702: If the compliance result indicates that the analysis keywords are compliant, perform a header matching check on the target processing file based on the second data column name to obtain the second result.

[0118] In step S701 of some embodiments, referring to Figure 8 If the target analysis mode is determined to be Pareto analysis according to the above method, the analysis keywords are obtained by the user entering them in the target processing parameter input box 801 in the Pareto analysis interface, and the second data column name is also obtained. Compliance detection refers to checking the validity and repetition of each analysis keyword setting, that is, requiring that the analysis keywords are not empty and not repeated. Compliance detection is performed on the analysis keywords, and the corresponding compliance results are obtained.

[0119] In step S702 of some embodiments, if the compliance result indicates that the analysis keywords are compliant (i.e., the analysis keywords are not empty and not repeated), then a header matching check is performed based on the second data column name to determine whether there is data in the header data of the target processing file that matches the second data column name, thus obtaining a second result. It is understood that the method for performing header matching checks based on the second data column name is similar to the method for performing header matching checks based on the first data column name, and this will not be described in detail in the embodiments of this application. If the compliance result indicates that the analysis keywords are non-compliant (i.e., the analysis keywords are empty, repeated, or at least one other condition), then a pop-up window or similar method can be used to remind the user to re-enter compliant analysis keywords.

[0120] The advantage of steps S701 to S702 is that before processing the target winding data, compliance checks are performed on the analysis keywords to determine whether the analysis keywords are compliant. This reduces the possibility of processing the target winding data based on non-compliant analysis keywords, thereby improving the accuracy of the processing results.

[0121] It is understood that in some embodiments, the method for obtaining target wrap data in Pareto analysis is the same as the method for obtaining target wrap data in Cpk analysis. Specifically, if the second result indicates that the target processing file includes a table header matching the second data column name, the column index of the second data column name in the target processing file is obtained to obtain the second data column index. The corresponding data in the target processing file is located and obtained based on the second data column index to obtain the target wrap data. It is understood that when the target processing file includes multiple rows of empty data, a step-out reading can be set. If the target processing file includes multiple tables, it can be set to automatically read the next table after step-out reading, until all tables have been read.

[0122] Reference Figure 9 In some other embodiments, step S104 includes, but is not limited to, steps S901 to S905.

[0123] Step S901: If the target winding data does not match the preset qualified data, match the target winding data with the analysis keywords to obtain the matching result;

[0124] Step S902: If the matching result indicates that the target winding data matches the analysis keyword, the first matching quantity is obtained;

[0125] Step S903: If the matching result indicates that the target winding data does not match the analysis keywords, generate winding keywords based on the target winding data;

[0126] Step S904: Obtain the second matching quantity based on the winding keywords and target winding data;

[0127] Step S905: Obtain the processing result based on the first matching quantity, the second matching quantity, the analyzed keywords, and the wrapped keywords.

[0128] In step S901 of some embodiments, preset qualified data is used to distinguish whether the target winding data corresponds to qualified products or unqualified products. Therefore, the preset qualified data can be set as the string value of qualified products. Each target winding data is compared with the preset qualified data. If the target winding data contains the preset qualified data, it means that the target winding data matches the preset qualified data. If the target winding data does not contain the preset qualified data, it means that the target winding data does not match the preset qualified data. Specifically, it can be determined whether the target winding data contains the preset qualified data by calling string.contains(). In the case that the target winding data does not match the preset qualified data, the target winding data is matched and compared with the analysis keywords to obtain the matching result.

[0129] In step S902 of some embodiments, if the matching result indicates that the target winding data matches the analysis keyword, that is, the target winding data includes the analysis keyword, then the matching count corresponding to the analysis keyword is incremented by 1. The first matching data refers to the number of target winding data corresponding to the analysis keyword. Taking five analysis keywords, including analysis keyword key1, analysis keyword key2... analysis keyword key5, as an example, a counting dictionary is pre-set for each analysis keyword. For example, the counting dictionary for analysis keyword key1 can be D1(key1, count1). The initial value of count1 in the counting dictionary is 0. When the target winding data matches the analysis keyword key1, count1 will be incremented by 1. The first matching count is the value of count1 after matching all target winding data with analysis keyword key1.

[0130] Understandably, when target wrapper data matches multiple analytics keywords simultaneously, the match count is based on the keyword that appears first. For example, if target wrapper data matches both analytics keyword 'key1' and analytics keyword 'key2', if 'key1' appears first, then 'count1' will be incremented by 1. If 'key2' appears first, then 'count2' will be incremented by 1. It's also understandable that the order of analytics keywords can be determined by comparing keyword indexes.

[0131] In step S903 of some embodiments, if the matching result indicates that the target wrapping data does not match any of the analysis keywords, a new analysis keyword is generated based on the target wrapping data, i.e., a wrapping keyword is generated. It is understood that the wrapping keyword can be determined by setting the number of characters in the keyword. For example, if the number of characters is set to 40 (i.e., 20 characters), when the number of characters corresponding to the target wrapping data is less than or equal to 40, all characters corresponding to the target wrapping data are used as wrapping keywords. When the number of characters corresponding to the target wrapping data is greater than 40, the characters corresponding to the first 40 characters of the target wrapping data are taken as wrapping keywords. It is understood that the embodiments of this application do not specifically limit the method for determining the wrapping keyword.

[0132] Understandably, a total number of keywords can be set (e.g., 19). If, when the total number of wrapping keywords and analyzed keywords equals the total number of keywords, there are still instances where the target wrapping data does not match the analyzed keywords, or vice versa, then "Other" keywords are generated. The number of these mismatches is used as the number of matches for the "Other" keywords.

[0133] In step S904 of some embodiments, the processing result means that the distribution of all target winding data can be determined based on the first matching quantity corresponding to the analysis keyword and the second matching quantity corresponding to the winding keyword, and then the cause of non-conformity can be analyzed based on the distribution.

[0134] In some embodiments, the processing results can also be visualized, that is, image processing can be performed based on the processing results and the target winding data to obtain, for example... Figure 8 The "NG Details Pareto Distribution" chart (i.e., the wrap-around analysis chart) is shown in the middle. Specifically, the first and second match counts are bubble sorted together, and the Pareto distribution chart is displayed based on the sorting results and the corresponding keywords (analysis keywords or wrap-around keywords). In the Pareto distribution chart, the horizontal axis represents the keywords (analysis keywords or wrap-around keywords), and the vertical axis represents the corresponding match counts (first match count and second match count) and cumulative percentage. It is understood that in this embodiment, the content of the horizontal and vertical axes is used as a preset display template. According to the actual analysis needs, the content of the horizontal and vertical axes can be adjusted, that is, the preset display template can be adjusted, and this embodiment does not specifically limit this.

[0135] In some embodiments, after each visualization process is completed, it is possible to perform operations such as... Figure 8 Take a screenshot of the interface shown and save the image to the corresponding file path, such as the "Data Analysis Results" file path. Alternatively, you can... Figure 8In the file selection box 802, select the file path for "Data Analysis Results" to view the corresponding visualization screenshots of historical processing results.

[0136] Reference Figure 10 This application also provides a winding data processing apparatus to implement the above-described winding data processing method. The apparatus includes:

[0137] The target data acquisition module 1001 is used to acquire target processing parameters, target processing files, and target analysis modes.

[0138] The parameter checking module 1002 is used to check the target processing parameters according to the target analysis mode and obtain the check results.

[0139] The winding data acquisition module 1003 is used to acquire target winding data based on the inspection results and the target processing file.

[0140] The winding data processing module 1004 is used to process the target winding data according to the target analysis mode and obtain the processing results.

[0141] The specific implementation of the winding data processing device is basically the same as the specific embodiment of the winding data processing method described above, and will not be repeated here.

[0142] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method for processing wound data. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0143] Reference Figure 11 , Figure 11 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0144] The processor 1101 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0145] The memory 1102 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1102 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1102 and is called and executed by the processor 1101 using the data processing method of the embodiments of this application.

[0146] Input / output interface 1103 is used to implement information input and output;

[0147] The communication interface 1104 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0148] Bus 1105 transmits information between various components of the device (e.g., processor 1101, memory 1102, input / output interface 1103, and communication interface 1104);

[0149] The processor 1101, memory 1102, input / output interface 1103 and communication interface 1104 are connected to each other within the device via bus 1105.

[0150] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for processing wound data.

[0151] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0152] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0153] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0154] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0156] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0157] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0159] The units described above 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.

[0160] Furthermore, 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it 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 all or part 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 multiple 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 of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0162] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for processing wound data, characterized in that, The method includes: Obtain target processing parameters, target processing files, and target analysis modes; The target processing parameters are checked according to the target analysis mode to obtain the check results; Obtaining target winding data based on the inspection results and the target processing file includes: if the inspection results indicate that the target processing parameters meet the requirements of the target analysis mode, obtaining the target winding data from the target processing file; The target winding data is processed according to the target analysis mode to obtain the processing result; The target analysis mode includes a first mode, which is Cpk analysis. The target processing parameters include processing limits and a first data column name. The processing limits include limits corresponding to the warning line and limits corresponding to the control line. The inspection results include a first result. And / or, the target analysis mode includes a second mode, which is Pareto analysis. The target processing parameters include analysis keywords and a second data column name. The inspection results include a second result. The step of checking the target processing parameters according to the target analysis mode and obtaining the check results includes: If the target analysis mode is the first mode, the processing limits are sorted to obtain the target sorting result; if the target sorting result is equal to the preset sorting result, the target processing file is checked for header matching according to the first data column name to obtain the first result. If the target analysis mode is the second mode, a compliance check is performed on the analysis keywords to obtain a compliance result; if the compliance result indicates that the analysis keywords are compliant, a header matching check is performed on the target processing file according to the second data column name to obtain the second result.

2. The method according to claim 1, characterized in that, The step of obtaining target winding data based on the inspection results and the target processing file includes: If the first result indicates that the target processing file includes a table header that matches the first data column name, the first data column index is obtained from the target processing file based on the first data column name; The target winding data is obtained based on the index of the first data column.

3. The method according to claim 2, characterized in that, The target winding data is processed according to the target analysis mode to obtain the processing result, including: If the target analysis mode is the first mode, the target winding data is compared with the processing limit to obtain a comparison result; The superiority rate is calculated based on the comparison results to obtain the superiority rate value; The target winding data is sorted to obtain the maximum winding data and the minimum winding data; The target winding data is calculated based on the maximum winding data and the minimum winding data to obtain the standard deviation; The process stability of the target winding data is calculated based on the standard deviation to obtain a stable value. The processing result is obtained based on the goodness-of-performance value and the stability value.

4. The method according to claim 1, characterized in that, The target winding data is processed according to the target analysis mode to obtain the processing result, including: If the target winding data does not match the preset qualified data, the target winding data is matched with the analysis keywords to obtain the matching result; If the matching result indicates that the target winding data matches the analysis keyword, the first matching quantity is obtained; If the matching result indicates that the target winding data does not match the analysis keywords, winding keywords are generated based on the target winding data; The second matching quantity is obtained based on the winding keywords and the target winding data; The processing result is obtained based on the first matching quantity, the second matching quantity, the analysis keyword, and the winding keyword.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Based on the processing results and the target winding data, image processing is performed to obtain a winding analysis diagram; The winding analysis diagram is displayed according to the preset display template.

6. A processing apparatus for wound data, characterized in that, The device includes: The target data acquisition module is used to acquire target processing parameters, target processing files, and target analysis modes; The parameter checking module is used to check the target processing parameters according to the target analysis mode and obtain the check results. A winding data acquisition module is used to acquire target winding data based on the inspection result and the target processing file, including: if the inspection result indicates that the target processing parameters meet the requirements of the target analysis mode, acquiring the target winding data from the target processing file; The winding data processing module is used to process the target winding data according to the target analysis mode to obtain the processing result; The target analysis mode includes a first mode, which is Cpk analysis. The target processing parameters include processing limits and a first data column name. The processing limits include limits corresponding to the warning line and limits corresponding to the control line. The inspection results include a first result. And / or, the target analysis mode includes a second mode, which is Pareto analysis. The target processing parameters include analysis keywords and a second data column name. The inspection results include a second result. The step of checking the target processing parameters according to the target analysis mode and obtaining the check results includes: If the target analysis mode is the first mode, the processing limits are sorted to obtain the target sorting result; if the target sorting result is equal to the preset sorting result, the target processing file is checked for header matching according to the first data column name to obtain the first result. If the target analysis mode is the second mode, a compliance check is performed on the analysis keywords to obtain a compliance result; if the compliance result indicates that the analysis keywords are compliant, a header matching check is performed on the target processing file according to the second data column name to obtain the second result.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

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