Automatic conversion method and system for cable point table

Abstract

The application provides an automatic conversion method and system of a cable point table, which is applied to the fields of spacecraft manufacturing and automatic test technology, and through traversing a source table file and reserving an effective worksheet, a table header row and a starting data row of the effective worksheet are automatically identified; by using a fuzzy matching algorithm based on string similarity, heterogeneous table header fields are adaptively aligned, and downward filling is performed on a merged cell to prevent core information loss, so that repaired structured data is obtained. Subsequently, the system automatically identifies special structures such as “scattered wires” and “grounding sheets” and standard structures through deep behavior type determination, and according to preset rules corresponding to the structures, data is reorganized, a unified standard connection relationship record directly adapting to test equipment logic is standardized generated, and finally, the result is written into a standard file output. The scheme realizes zero-intervention full-automatic conversion of multi-source and multi-format cable tables, and has strong special cable structure and abnormal data processing capacity.

Description

Technical Field

[0001] This application relates to the fields of spacecraft manufacturing and automated testing technology, specifically to an automatic conversion method and system for cable location tables. Background Technology

[0002] Cable assemblies are a crucial component of spacecraft electrical systems, and their connection reliability directly impacts the safety and stability of the entire system. During spacecraft assembly, testing, and mass production, cables must undergo electrical performance tests, including continuity, insulation, and withstand voltage tests, after fabrication to ensure the absence of issues such as incorrect connections, missing connections, or short circuits.

[0003] With the increasing intensity of aerospace missions and the growing complexity of cable assemblies, the demand for automated cable testing is growing. The efficient operation of automated testing equipment relies heavily on accurate records of standard connection points. While existing solutions mostly rely on specialized software for parsing and conversion, achieving automatic conversion from contact tables to test procedures, they still have the following shortcomings in practical engineering applications when faced with diverse and non-standard raw data: First, the connection point table lacks format compatibility and cannot handle raw data from diverse sources with chaotic formats. Even assuming that the connection point table provided by the design unit has a certain standardized format and that the design document makes uniform requirements for the format, in actual production, the cable point table comes from different software (such as CAD, EDA, etc.), and the writing habits and naming conventions provided by different designers, different projects, and even different collaborating units are not the same. This results in these source table files exhibiting extremely high diversity and format uncertainty. When faced with raw tables in unexpected formats, the existing solutions often directly report errors or fail to parse, and manual intervention is still required for format preprocessing. Second, there are a large number of special structures such as loose wires and grounding plates in the aerospace cable network. Their expression in the original wiring table is varied and usually lacks structured field definitions, which leads to a deviation between the existing converted data and the actual test logic of the test equipment. Manual correction is still required for each item. Third, existing conversion solutions cannot effectively handle table files with merged cells. During parsing, they often only extract the first row of data from the merged cells, resulting in the loss of key information such as connector numbers and causing data association errors.

[0004] Therefore, a new automatic conversion scheme for cable location tables is needed. Summary of the Invention

[0005] In view of this, the embodiments of this specification provide an automatic conversion method and system for cable location tables, which solves the problems of low test data preparation efficiency, excessive manual intervention, and high error risk caused by the diverse source table file formats and frequent abnormal data in the prior art.

[0006] The embodiments in this specification provide the following technical solutions: This specification provides an embodiment of an automatic conversion method for cable location tables, including: Obtain the source spreadsheet file, traverse the worksheets in the source spreadsheet file, and obtain the valid worksheets; Perform data region identification on each of the valid worksheets to obtain valid data regions, wherein the valid data regions include header rows and data start rows; Extract the header fields from each column of the header row, match the header fields with keywords in a preset rule base, and establish a field mapping relationship between the header fields and target fields. The target fields include at least a start connector, a start pin, an end connector, and an end pin. When the header fields do not completely match the keywords, calculate the similarity between the header fields and each keyword according to a string similarity algorithm, and take the target field corresponding to the keyword with the highest similarity as the mapping result. Based on the field mapping relationship and the starting row of the data, it is detected whether there are merged cells in the effective data area. If so, the effective data in the merged cells is filled into the remaining empty cells in the merged cells to obtain the repaired structured data. Read the repaired structured data line by line, and determine the cable structure type corresponding to each line of structured data based on the features of the fields in the line and the keyword recognition rules; The system invokes a preset conversion rule corresponding to the cable structure type, determines the electrical nodes participating in the continuity test based on the starting connector, starting pin, ending connector, and ending pin in each of the structured data, establishes a continuity relationship mapping between the electrical nodes, and adjusts the data arrangement matrix and the correspondence between electrical nodes according to the continuity relationship mapping to generate a standard connection relationship record that can be recognized by the test equipment, so that the test equipment can perform cable continuity tests. According to the preset format requirements, the standard connection relationship records are written into the result file and output.

[0007] Furthermore, the cable structure types include loose wire structure, grounding plate structure, and standard cable structure; the step of calling the preset conversion rule corresponding to the cable structure type to generate a standard connection relationship record that can be recognized by the test equipment includes: If the cable structure type is determined to be a loose cable structure, the corresponding structured data is normalized and converted into two standard connection relationship records to meet the bidirectional continuity test requirements; one standard connection relationship record starts from the corresponding pin of the connector to which the loose cable is connected and ends at the first normalized identifier; the other standard connection relationship record starts from the second normalized identifier and ends at the corresponding pin of the connector to which the loose cable is connected. If the cable structure type is determined to be a grounding plate structure, the corresponding structured data is normalized and converted into a standard connection relationship record. The standard connection relationship record starts from the corresponding pin of the connector connected to the grounding plate and ends with the third normalized identifier. If the cable structure type is determined to be a standard cable structure, the starting connector, starting pin information, ending connector, and ending pin information in the corresponding structured data are extracted and normalized into a single standard connection relationship record.

[0008] Further, the step of performing data region identification on each of the valid worksheets to obtain valid data regions includes: The worksheet data parsing engine is invoked to scan the first preset number of rows of each valid worksheet, and the preset field names are found through the keyword matching algorithm. When at least two rows with the preset field names are detected, the rows with the at least two preset field names are determined to be the header rows. The row following the header row is determined as the starting row of the data.

[0009] Furthermore, the preset rule base is constructed in the following way: Multiple header patterns and column name keywords are predefined and used to match the header fields to determine the target field type; Predefined type identification keywords are used to match the inline field text in the structured data of each row to determine the cable structure type.

[0010] Furthermore, the automatic conversion method for the cable location table also includes: There are multiple source table files; The batch processing engine is invoked to create independent parallel conversion tasks for each of the source table files. After the conversion is complete, the conversion results of each valid worksheet will be merged and written into the same unified standard result file; Output a summary statistical transformation log report.

[0011] Furthermore, the automatic conversion method for the cable location table also includes: When performing data area identification on each of the valid worksheets, if the valid data area cannot be identified within the first preset number of rows of the worksheet, the identification failure status is returned and a prompt is sent to the user interface so that the user can manually specify the header row on the user operation interface. The system receives the field mapping relationship that the user has manually adjusted and determined, and saves the adjusted field mapping relationship as a mapping configuration to the preset rule base.

[0012] Furthermore, the automatic conversion method for the cable location table also includes: If a data defect is detected in the structured data, the row corresponding to the data defect is marked as an abnormal row, and an error list file is output. And / or, display the abnormal line on the user interface so that the user can manually edit or ignore it on the interface.

[0013] This specification also provides an automatic conversion system for cable location tables, comprising: The data parsing module is used to obtain the source table file, traverse the worksheets in the source table file, and obtain the valid worksheets; the data parsing module includes a format recognition module and a field mapping module; The format recognition module is used to perform data area recognition on each of the valid worksheets to obtain a valid data area, wherein the valid data area includes a header row and a data start row; The field mapping module is used to extract the header fields of each column in the header row, match the header fields with keywords in a preset rule base, and establish a field mapping relationship between the header fields and target fields. The target fields include at least a start connector, a start pin, an end connector, and an end pin. When the header fields do not completely match the keywords in the preset rule base, the similarity between the header fields and each keyword is calculated according to a string similarity algorithm, and the target field corresponding to the keyword with the highest similarity is taken as the mapping result. The data conversion module, connected to the data parsing module, is used to detect whether there are merged cells in the effective data area based on the field mapping relationship and the starting row of the data. If there are, the effective data in the merged cells is filled into the remaining empty cells in the merged cells to obtain the repaired structured data. The repaired structured data is read line by line, and the cable structure type corresponding to each row of structured data is determined based on the characteristics of the fields in the row and the keyword recognition rules. The preset conversion rules corresponding to the cable structure type are called, and the electrical nodes participating in the continuity test are determined based on the starting connector, starting pin, ending connector, and ending pin in each of the structured data. A continuity relationship mapping between electrical nodes is established, and the data arrangement matrix and the correspondence between electrical nodes are adjusted according to the continuity relationship mapping to generate a standard connection relationship record that can be recognized by the test equipment for the test equipment to perform cable continuity testing. The output management module, connected to the data conversion module, is used to write the standard connection relationship records into a result file and output them according to preset format requirements.

[0014] Furthermore, the automatic conversion system for the cable location table also includes: The user interaction module is connected to both the data parsing module and the output management module. It provides a graphical user interface for users to import source spreadsheet files, switch between worksheets, preview data, and receive and export result files transmitted by the output management module.

[0015] Furthermore, the user interaction module is also used to provide a prompt and display a table preview area when the data parsing module cannot identify the valid data area within the first preset number of rows, so that the user can manually specify the header row through the table preview area; The system receives manually adjusted field mapping relationships from the user and, upon receiving a confirmation instruction, transmits these field mapping relationships as mapping configurations to the format recognition and field mapping module to update the preset rule base.

[0016] Compared with the prior art, the technical effects that can be achieved by at least one of the above-mentioned technical solutions adopted in the embodiments of this specification include at least the following: 1. By identifying and locating data regions and mapping intelligent fields based on string similarity, the compatibility problem caused by the diverse formats and different column names of the source table files is effectively solved. The processing time of a single complex cable location table is greatly reduced from 30 minutes in the traditional manual mode to less than 5 seconds. The data processing speed has achieved a leap from "minute level" to "second level", easily meeting the massive data throughput requirements brought about by the mass production of microsatellites and spacecraft. 2. By performing data repair and reorganization through standardized and structured algorithmic logic, and introducing an automatic data repair mechanism for merged cells at the underlying level, the system fundamentally eliminates errors in structured data association caused by missing key fields. In addition, it automatically adapts to complex cable structures such as loose wires and grounding plates, realizing intelligent conversion of the entire process from multi-source, non-standard process tables to data that can be identified by test equipment. This completely eliminates the risk of misjudgment and missed testing caused by test data errors, providing a solid guarantee for the electrical safety of aerospace products.

[0017] 3. It simplifies the process flow from design to testing, reducing the complex long chain of "design export, manual screening, format adjustment, secondary verification, and equipment import" in the traditional process to a short automated chain of "one-click import and automatic output". This allows non-professionals to quickly complete data preparation, which not only significantly lowers the operational threshold for data preparation, but also breaks down the data barriers from digital design to digital manufacturing, providing key data support for enterprises' intelligent manufacturing and digital transformation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the automatic conversion method of the cable location table in a specific embodiment of this application; Figure 2 This is a flowchart of the software system module architecture in a specific embodiment of this application; Figure 3 This is a flowchart of data parsing and conversion in a specific embodiment of this application; Figure 4 This is a flowchart of abnormal data processing in a specific embodiment of this application; Figure 5 This is a batch processing flowchart in a specific embodiment of this application; Figure 6 This is a user interface interaction flowchart in a specific embodiment of this application. Detailed Implementation

[0020] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0021] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0023] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the shape, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0024] Additionally, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that practice can be carried out without these specific details.

[0025] Regarding existing automatic conversion schemes for cable location tables, such as the prior art mentioned in the background section, through problem analysis and solution exploration, it was found that: on the one hand, the current aerospace cable design field lacks a unified standard for cable location table data. The data output formats of various design units and design software are independent and significantly different, which poses a fundamental obstacle to automated data processing. On the other hand, existing solutions mainly focus on the test program generation and transfer cable management stages, while paying insufficient attention to the original data parsing and format adaptation stages, lacking a universal, configurable, and intelligent data format recognition and conversion framework.

[0026] In view of this, the embodiments of this specification propose an automatic conversion scheme for cable location tables. The overall idea is as follows: First, by traversing all worksheets in the source table file, valid worksheets are automatically retained, and the header row and starting data row of each valid worksheet are identified. Then, the header fields are automatically identified, and a fuzzy matching algorithm based on string similarity is introduced to adaptively align heterogeneous header fields caused by diverse design sources. Downfilling is performed on merged cells to prevent the loss of core fields in non-first rows. Finally, by performing deep behavior type determination based on field features and keywords on the repaired structured data, special structures or standard structures such as "loose wires" and "grounding plates" are distinguished and reconstructed. These structures are standardized and converted into unified standard connection relationship records that can directly adapt to the operating logic of test equipment. The fully automatic conversion from the standard format of test equipment can be completed without manual intervention, and it has the ability to automatically identify and standardize special cable types such as loose wires and grounding plates, as well as abnormal data such as merged cells.

[0027] The technical solutions provided by the various embodiments of this application are described below with reference to the accompanying drawings.

[0028] like Figure 1 and Figure 3 As shown in the embodiments of this specification, an automatic conversion method for cable location tables is provided, including: Step S10: Obtain the source table file, traverse the worksheets in the source table file, and obtain the valid worksheets.

[0029] Specifically, the system receives raw table data of cables to be processed, such as one or more source Excel files imported by the user through a graphical interface. After receiving the source table file, the system traverses all worksheets in each source table file, automatically identifies and filters out empty or invalid worksheets, and selects valid worksheets for subsequent parsing.

[0030] Step S20: For each valid worksheet selected, call the Excel data parsing engine (such as Excel Data Parsing Engine) to automatically identify the start and end rows of the data range, as well as the row containing the table header.

[0031] Step S30: After locking the valid data area, extract the original header fields of each column in the header row, and perform field normalization mapping using a preset rule base to establish the field mapping relationship between the header fields and the target fields. Specifically: The extracted header fields are compared one by one with the keywords in the preset rule base. When the header field cannot be precisely matched with any keyword in the preset rule base due to different design sources or writing habits, the fuzzy matching mechanism is activated to calculate the similarity value between the header field and each keyword in the rule base. The keyword with the highest similarity is selected, and the target field corresponding to the keyword is used as the final mapping result, thereby establishing the field mapping relationship between heterogeneous header fields and target fields.

[0032] Step S40: After completing the field mapping of the header row, read the data row by row according to the field mapping relationship, starting from the first data row, and check whether there are merged cells in the valid data area. Figure 4 As shown, if the existence of a merged cell is detected, the valid data in the merged cell is automatically filled down into the remaining empty cells within the merged cell, ensuring that each data record contains complete connector information and eliminating association errors caused by missing information.

[0033] Step S50: Read the repaired structured data line by line. During the reading process, perform type judgment on each line of data to determine whether the line of data belongs to a conventional double-ended direct connection structure or a non-standard connection structure with special process requirements.

[0034] Based on the determined cable structure type, the preset conversion rule bound to that cable structure type is invoked to logically reorganize the current structured data. It should be noted that the conversion rule will dynamically adjust the data arrangement matrix, conduction relationship mapping, and electrical node correspondence according to different structure types, reorganizing the original table records and generating standard connection relationship records that can be directly read, parsed, and executed by external automated testing equipment. The standard connection relationship record includes at least the following fields: starting connector, starting pin, ending connector, ending pin, and cable model.

[0035] Step S60: Write all the converted standard connection relationship records into a unified result file and output it.

[0036] This application achieves high-precision, robust, and fully automated conversion from multi-source process point tables to standard connection records for test equipment through intelligent positioning and mapping of heterogeneous table areas, adaptive repair of merged cells, and automated type determination and reorganization of cable structures. It fundamentally changes the inefficient traditional manual processing or simple script-assisted model, achieving a leap in data processing speed. By replacing tedious repetitive labor with automated processing, it eliminates reliance on experience in manual copying, pasting, and formatting adjustments, reducing manual time spent on test data preparation by over 90%. This frees technicians from low-value formatting work, allowing them to focus on higher-value technical review, significantly reducing labor costs. Furthermore, thanks to the improved data accuracy, it effectively avoids troubleshooting and cable repair caused by false alarms in cable testing, saving production rework costs.

[0037] In some embodiments, such as Figure 3 As shown, the system reads the repaired structured data line by line and performs intelligent recognition based on predefined type identification keywords and features in the rule base: If a line of data is identified as a "loose wire," meaning that one end of the cable is not connected to a connector but directly grounded or connected to the housing, the line of data is automatically converted into two standard connection relationship records: the first record starts at the corresponding pin of the connector to which the loose wire is actually connected and ends at the preset first normalized identifier, such as the system default or user preset "housing" or "ground"; the second record starts at the second normalized identifier, such as "housing" or "ground," and ends at the corresponding pin of the connector to which the loose wire is actually connected. This generates bidirectional records to meet the requirements of the test equipment for bidirectional continuity testing.

[0038] If a line of data is identified as "grounding plate", meaning that the cable is connected to the connector housing or chassis ground through the grounding plate, a standard connection record is automatically generated. The starting point is the corresponding pin of the connector to which the grounding plate is connected, and the ending point is the third normalized identifier, such as "chassis ground" or "housing ground".

[0039] For ordinary data with complete fields, the system determines that it is a standard cable structure. According to the field order, field name and data type required by the target test equipment, it is reorganized into a standard format data record. For example, the starting connector, starting pin, ending connector and ending pin information can be directly extracted and standardized into a single standard connection relationship record.

[0040] In some embodiments, the source table file adopts a common spreadsheet format. When the system calls the worksheet data parsing engine to identify the region of the valid worksheet, it will selectively scan the first preset number of rows of the worksheet (such as the first 20 rows), identify the starting area of ​​the data through the built-in keyword matching algorithm, match preset field names such as "connector code", "needle number", "thread number", "from", "to", and support fuzzy matching. When at least two preset field names that meet the requirements are detected in a certain row, the row is determined to be the header row, and the row immediately following the header row is automatically determined to be the data starting row.

[0041] In some embodiments, a configurable rule base is pre-built, which predefines various header patterns and column name keywords to handle common naming variations of fields such as "connector number," "connector code," "device code," "interface code," "pin number," "pin number," "wire number," and "signal name," in order to determine the target field type. During mapping, if the original header field completely matches the keyword in the rule base, the mapping is established directly; if it does not completely match, the module will start a fuzzy matching algorithm to calculate the string similarity between the header field and each keyword in the rule base, and automatically select the target field corresponding to the keyword with the highest similarity as the mapping result. Through this mechanism, the system summarizes and maps each column of the source table into seven standard target fields: starting connector, starting pin, ending connector, ending pin, cable model, cable color, and remarks.

[0042] The rule base also predefines identification keywords for special cable types such as loose wires and grounding plates.

[0043] In some embodiments, such as Figure 5 As shown, when the system is faced with multiple source table files imported at once in large-scale production, the batch processing engine will be automatically activated.

[0044] Specifically, by utilizing the computing resources of multi-core CPUs, independent and isolated parallel conversion tasks are created for each imported source table file. The parallel flow of multiple tasks significantly reduces the overall queuing time for massive files.

[0045] After all parallel tasks have been completed, the standard transformation results of each valid worksheet are merged and written to a single generated result file. For Excel files containing multiple source worksheets, the output result file will retain the corresponding number of target worksheets, with each target worksheet named the same as or according to preset rules.

[0046] In some embodiments, a detailed summary conversion log report is automatically generated at the same time as the conversion output. The report clearly records the processing status of each source file, the number of rows successfully processed in each worksheet, the types and quantities of special cables (spread wires, grounding plates) identified, the conversion time, and any abnormal data and repair methods. After the conversion is completed, a conversion report is generated and provided to the user for preview.

[0047] In some embodiments, if the format of the input source table is extremely irregular (e.g., the first few rows contain a large number of process notes or meaningless blank lines), causing the format recognition module to fail to match any preset keywords within the first preset number of rows and return a recognition failure status, a warning message will be immediately sent to the user interface, and a clear preview area of ​​the original table data will be displayed simultaneously.

[0048] It also allows users to manually click on the specified actual header row on the interface. After receiving the field mapping relationship manually adjusted and confirmed by the user, the adjusted field mapping relationship is dynamically saved as a new mapping configuration to the preset rule base so that it can be automatically recognized when encountering tables with the same characteristics next time.

[0049] In some embodiments, if the system detects serious data defects in the structured data during the conversion process that cannot be automatically completed by rules or downfill (such as a row where both the connector name and pin number are empty, resulting in a complete break in the connection), the system will not directly report an error and suspend the process. Instead, it will mark the row corresponding to the data defect as an abnormal row "to be manually processed". A separate error list file can be generated in the final output. These abnormal rows can also be highlighted on the graphical user interface, allowing technicians to manually edit and correct the defective fields directly on the interface, or choose to ignore and skip them, and then re-trigger the conversion.

[0050] Next, we will further illustrate this solution with specific examples.

[0051] This application provides an automatic conversion scheme for cable location tables, which is used to automatically convert cable connection tables from different sources and in different formats into a standard format that can be recognized by test equipment. An Excel spreadsheet is used as an example below.

[0052] Example 1: Basic Conversion Process - Automatic Recognition and Conversion of Standard Excel Spreadsheets Assuming the input file is "Type A Cable Wiring Table.xlsx", the table has a standard structure, including a fixed header row and a data start row.

[0053] like Figure 2 and Figure 3As shown, the user interface module 1 of the user interaction layer first responds to external trigger commands to activate the data import program. Then, the target Excel file is imported through the input module 2 of the data input layer. The file input module 2 supports .xlsx and .xls formats and can import one or more files at a time. After import, the data parsing module 3 of the data parsing layer automatically performs data parsing. Its internal format recognition unit 3a automatically scans the first N rows (e.g., the first 20 rows) of the worksheet and identifies the starting area of ​​the data using a keyword matching algorithm. Specifically, the format recognition unit 3a has a built-in keyword library containing common field names such as "connector code," "needle number," "thread number," "from," and "to," and supports fuzzy matching. When at least two keywords are detected in a row, that row is determined to be the header row, and the next row immediately following the header row is automatically taken as the starting row of the data.

[0054] Subsequently, the field mapping unit 3b reads the original text of each column in the header row column by column and establishes a mapping relationship with the preset target fields. The preset target fields include: Connector A Name, Pin A Number, Connector B Name, Pin B Number, and Cable Type. During the mapping process, if the original header column name matches the target field exactly, the mapping relationship is established directly; if it does not match exactly, the field mapping unit 3b initiates fuzzy matching and synonym replacement (e.g., mapping "Connector Number" to "Connector A Name"). In this embodiment, the source table header contains standard column names such as "Connector Code" and "Pin Number," and the field mapping is directly matched successfully.

[0055] After receiving the parsed structured data, the data conversion module 4 of the conversion processing layer uses its internal standard format conversion unit 4a to convert each line of raw data into the format required by the test equipment: <Connector A Name> - <Pin A Number>, <Connector B Name> - <Pin B Number>, <Cable Type>. During the conversion process, because the source table data has no special structure and no data anomalies, the loose wire normalization unit 4b and the anomaly repair unit 4c are not triggered.

[0056] Finally, the output module 5 of the output management layer generates a new xlsx file from the transformed data (i.e., the standard join relationship) and saves it in the output directory specified by the user. Simultaneously, the output module 5 records transformation statistics (total number of rows, number of successful rows, number of failed rows) and writes them to a log file in the same directory. Users can preview the data before and after transformation and export the results through the user interface module 1.

[0057] Example 2: Special Data Processing - Automatic Standardization of Loose Wires and Grounding Plates Assume the input file is a "Type B Cable Wiring Table.xlsx" containing special structures for loose wires and grounding plates. Loose wires refer to cables with one end free and not connected to connector pins, while grounding plates refer to special cable structures used for grounding. For this type of special data, which is highly prone to errors during manual processing, automated reorganization and repair are performed using the loose wire normalization unit 4b and the anomaly repair unit 4c.

[0058] like Figure 2 and Figure 3 As shown, after the data parsing module 3 completes the field mapping, the data conversion module 4 detects special markers in each row. The loose wire normalization unit 4b has built-in loose wire identification rules: if the "Connector B Name" field is empty or contains keywords such as "loose wire," "empty," or "free," and the "Pin B Number" field is empty, it is determined to be a loose wire. For loose wires, the loose wire normalization unit 4b automatically sets the "Connector B Name" to "N / A" and sets the "Pin B Number" to "GND" or the user-preset default common ground terminal. In specific implementation, users can customize the default ground terminal identifier in the configuration file; the default value is "GND."

[0059] For grounding plates, the built-in identification rules of the loose wire standardization unit 4b are: the "Cable Type" field contains keywords such as "grounding plate", "ground", or "ground", or the "Connector B Name" field contains "PE" or "grounding bar". The loose wire standardization unit 4b treats grounding plates as special cables. When converting them to the standard format, it forces "Pin B" to be "PE" and appends the "(Ground)" mark after the cable type so that the test equipment can identify them.

[0060] In this embodiment, the anomaly repair unit 4c is used to handle the merged cell problem that often accompanies scattered lines or other special structures. For example, when the starting connector name of the scattered line in the original table is displayed in the form of a merged cell spanning multiple rows, the anomaly repair unit 4c automatically detects the merged cell area, performs a split operation, and fills in the values ​​downwards (that is, fills the remaining empty cells with the non-empty values ​​of the first row of the merged area) to ensure that the data in each row is complete.

[0061] Example 3: Batch processing, parallel conversion of multiple worksheets and multiple files Suppose that in a production workshop, dozens of cable wiring diagram files need to be converted at once, and each file contains multiple worksheets.

[0062] like Figure 2 and Figure 5As shown, using the "Batch Import" function in user interface module 1, the user selects the folder containing all Excel files to be converted. File input module 2 recursively scans all .xlsx and .xls files in that folder and generates a file list. For each file, the software performs the following operations: First, open the file and obtain a list of all worksheet names. Then, iterate through each worksheet sequentially, calling data parsing module 3 to check if the worksheet is empty or contains only invalid data. The specific criteria are: if the number of data rows after the header row is less than 1, or if all key fields in all data rows are empty, the worksheet is considered invalid and is directly filtered and skipped.

[0063] During batch processing, an independent conversion task is created for each file, and the tasks are executed in parallel to make full use of multi-core CPUs to improve efficiency. After the conversion is completed, the result output module 5 merges the conversion results of each worksheet into a unified output file, and generates a summary statistical report (including the number of successfully converted rows, the number of failed rows, and the time taken for each file and each worksheet).

[0064] Example 4: Exception Handling and User Intervention – Semi-Automatic Conversion When Format Cannot Be Automatically Recognized like Figure 6 As shown, suppose the imported source table file is an irregular "C-type cable table.xlsx". The first row of this table is empty, the second row is a meaningless comment, and the data begins from the third row. The column names use abbreviations such as "CON1", "PIN1", "CON2", and "PIN2". In this case, the format recognition unit 3a of the data parsing module 3 cannot match any preset keywords in the default first 20 rows and returns a recognition failure status.

[0065] At this point, the user interaction layer triggers an abnormal interaction prompt, displaying a message such as "Unable to automatically identify the data area, please manually specify the header row." The user can view the original data through the table preview area on user interface module 1 and click to select the header row. Subsequently, field mapping unit 3b displays a mapping table between the currently identified column names and the target field, allowing the user to manually adjust the mapping relationship. After completing the mapping settings, the user clicks "Confirm," and the system saves the mapping configuration to the local rule base, enabling automatic matching the next time a table with the same format is encountered.

[0066] During the data conversion process, the anomaly repair unit 4c is also responsible for handling unrepairable abnormal data. For example, if a row is found to have an empty connector name and pin number, which cannot be filled in by downfilling or using default values, the anomaly repair unit 4c marks the row as "pending manual processing," outputs a separate error list file in the conversion results, and highlights the abnormal row on the interface. The user can manually edit or ignore the row on the interface and then re-execute the conversion.

[0067] Experimental data shows that, compared with the traditional manual conversion method, this application can shorten the processing time of a single form to less than 5 seconds, improve the overall testing programming efficiency by more than 10 times, and maintain a 100% conversion accuracy rate. It effectively avoids human input errors, reduces rework costs, and effectively supports the digital and intelligent transformation of aerospace cable manufacturing.

[0068] Based on the same inventive concept, this application also provides an automatic conversion system for cable location tables, comprising: The data parsing module is used to obtain the source table file, traverse the worksheets in the source table file, and obtain the valid worksheets; the data parsing module includes a format recognition module and a field mapping module; The format recognition module is used to perform data area recognition on each of the valid worksheets to obtain a valid data area, wherein the valid data area includes a header row and a data start row; The field mapping module is used to extract the header fields of each column in the header row, match the header fields with keywords in a preset rule base, and establish a field mapping relationship between the header fields and target fields. The target fields include at least a start connector, a start pin, an end connector, and an end pin. When the header fields do not completely match the keywords in the preset rule base, the similarity between the header fields and each keyword is calculated according to a string similarity algorithm, and the target field corresponding to the keyword with the highest similarity is taken as the mapping result. The data conversion module, connected to the data parsing module, is used to detect whether there are merged cells in the effective data area based on the field mapping relationship and the starting row of the data. If there are, the effective data in the merged cells is filled into the remaining empty cells in the merged cells to obtain the repaired structured data. The repaired structured data is read line by line, and the cable structure type corresponding to each row of structured data is determined based on the characteristics of the fields in the row and the keyword recognition rules. The preset conversion rules corresponding to the cable structure type are called, and the electrical nodes participating in the continuity test are determined based on the starting connector, starting pin, ending connector, and ending pin in each row of structured data. A continuity relationship mapping between electrical nodes is established, and the data arrangement matrix and the correspondence between electrical nodes are adjusted according to the continuity relationship mapping to generate a standard connection relationship record that can be recognized by the test equipment for the test equipment to perform cable continuity testing. The output management module, connected to the data conversion module, is used to write the standard connection relationship records into a result file and output them according to preset format requirements.

[0069] In some embodiments, such as Figure 6As shown, the automatic conversion system for the cable location table also includes a user interaction module, which is connected to the data parsing module and the output management module respectively. It provides a graphical operation interface for users to import source table files, switch between worksheets and preview data, and receive and export the result files transmitted by the output management module.

[0070] In some embodiments, the user interaction module is further configured to provide a prompt and display a table preview area when the data parsing module cannot identify the valid data area within the first preset number of rows, so that the user can manually specify the header row through the table preview area; The system receives manually adjusted field mapping relationships from the user and, upon receiving a confirmation instruction, transmits these field mapping relationships as mapping configurations to the format recognition and field mapping module to update the preset rule base.

[0071] This application is developed using Python and supports the Windows operating system. During runtime, peak memory usage is kept below 500MB, and the conversion time for a single worksheet does not exceed 5 seconds.

[0072] In this specification, the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the descriptions of the embodiments described later are relatively simple, and relevant parts can be referred to the descriptions of the foregoing embodiments.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An automatic conversion method for cable location tables, characterized in that, include: Obtain the source spreadsheet file, traverse the worksheets in the source spreadsheet file, and obtain the valid worksheets; Perform data region identification on each of the valid worksheets to obtain valid data regions, wherein the valid data regions include header rows and data start rows; Extract the header fields from each column of the header row, match the header fields with keywords in a preset rule base, and establish a field mapping relationship between the header fields and target fields. The target fields include at least a start connector, a start pin, an end connector, and an end pin. When the header fields do not completely match the keywords, calculate the similarity between the header fields and each keyword according to a string similarity algorithm, and take the target field corresponding to the keyword with the highest similarity as the mapping result. Based on the field mapping relationship and the starting row of the data, it is detected whether there are merged cells in the effective data area. If so, the effective data in the merged cells is filled into the remaining empty cells in the merged cells to obtain the repaired structured data. Read the repaired structured data line by line, and determine the cable structure type corresponding to each line of structured data based on the features of the fields in the line and the keyword recognition rules; The system invokes a preset conversion rule corresponding to the cable structure type, determines the electrical nodes participating in the continuity test based on the starting connector, starting pin, ending connector, and ending pin in each of the structured data, establishes a continuity relationship mapping between the electrical nodes, and adjusts the data arrangement matrix and the correspondence between electrical nodes according to the continuity relationship mapping to generate a standard connection relationship record that can be recognized by the test equipment, so that the test equipment can perform cable continuity tests. According to the preset format requirements, the standard connection relationship records are written into the result file and output.

2. The automatic conversion method according to claim 1, characterized in that, The cable structure types include loose wire structure, grounding plate structure, and standard cable structure; the step of calling the preset conversion rule corresponding to the cable structure type to generate a standard connection relationship record that can be recognized by the test equipment includes: If the cable structure type is determined to be a loose cable structure, the corresponding structured data is normalized and converted into two standard connection relationship records to meet the bidirectional continuity test requirements; one standard connection relationship record starts from the corresponding pin of the connector to which the loose cable is connected and ends at the first normalized identifier; the other standard connection relationship record starts from the second normalized identifier and ends at the corresponding pin of the connector to which the loose cable is connected. If the cable structure type is determined to be a grounding plate structure, the corresponding structured data is normalized and converted into a standard connection relationship record. The standard connection relationship record starts from the corresponding pin of the connector connected to the grounding plate and ends with the third normalized identifier. If the cable structure type is determined to be a standard cable structure, the starting connector, starting pin information, ending connector, and ending pin information in the corresponding structured data are extracted and normalized into a single standard connection relationship record.

3. The automatic conversion method according to claim 1, characterized in that, The step of performing data region identification on each of the valid worksheets to obtain valid data regions includes: The worksheet data parsing engine is invoked to scan the first preset number of rows of each valid worksheet, and the preset field names are found through the keyword matching algorithm. When at least two rows with the preset field names are detected, the rows with the at least two preset field names are determined to be the header rows. The row following the header row is determined as the starting row of the data.

4. The automatic conversion method according to claim 1, characterized in that, The preset rule base is constructed in the following way: Multiple header patterns and column name keywords are predefined and used to match the header fields to determine the target field type; Predefined type identification keywords are used to match the inline field text in the structured data of each row to determine the cable structure type.

5. The automatic conversion method according to claim 1, characterized in that, The automatic conversion method for the cable location table also includes: There are multiple source table files; The batch processing engine is invoked to create independent parallel conversion tasks for each of the source table files. After the conversion is complete, the conversion results of each valid worksheet will be merged and written into the same unified standard result file; Output a summary statistical transformation log report.

6. The automatic conversion method according to claim 1, characterized in that, The automatic conversion method for the cable location table also includes: When performing data area identification on each of the valid worksheets, if the valid data area cannot be identified within the first preset number of rows of the worksheet, the identification failure status is returned and a prompt is sent to the user interface so that the user can manually specify the header row on the user operation interface. The system receives the field mapping relationship that the user has manually adjusted and determined, and saves the adjusted field mapping relationship as a mapping configuration to the preset rule base.

7. The automatic conversion method according to claim 1, characterized in that, The automatic conversion method for the cable location table also includes: If a data defect is detected in the structured data, the row corresponding to the data defect is marked as an abnormal row, and an error list file is output. And / or, display the abnormal line on the user interface so that the user can manually edit or ignore it on the interface.

8. An automatic conversion system for cable location tables, characterized in that, include: The data parsing module is used to obtain the source table file, traverse the worksheets in the source table file, and obtain the valid worksheets; the data parsing module includes a format recognition module and a field mapping module; The format recognition module is used to perform data area recognition on each of the valid worksheets to obtain a valid data area, wherein the valid data area includes a header row and a data start row; The field mapping module is used to extract the header fields of each column in the header row, match the header fields with keywords in a preset rule base, and establish a field mapping relationship between the header fields and target fields. The target fields include at least a start connector, a start pin, an end connector, and an end pin. When the header fields do not completely match the keywords in the preset rule base, the similarity between the header fields and each keyword is calculated according to a string similarity algorithm, and the target field corresponding to the keyword with the highest similarity is taken as the mapping result. The data conversion module, connected to the data parsing module, is used to detect whether there are merged cells in the effective data area based on the field mapping relationship and the starting row of the data. If there are, the effective data in the merged cells is filled into the remaining empty cells in the merged cells to obtain the repaired structured data. The repaired structured data is read line by line, and the cable structure type corresponding to each row of structured data is determined based on the characteristics of the fields in the row and the keyword recognition rules. The preset conversion rules corresponding to the cable structure type are called, and the electrical nodes participating in the continuity test are determined based on the starting connector, starting pin, ending connector, and ending pin in each of the structured data. A continuity relationship mapping between electrical nodes is established, and the data arrangement matrix and the correspondence between electrical nodes are adjusted according to the continuity relationship mapping to generate a standard connection relationship record that can be recognized by the test equipment for the test equipment to perform cable continuity testing. The output management module, connected to the data conversion module, is used to write the standard connection relationship records into a result file and output them according to preset format requirements.

9. The automatic conversion system for cable location tables according to claim 8, characterized in that, The automatic conversion system for the cable location table also includes: The user interaction module is connected to both the data parsing module and the output management module. It provides a graphical user interface for users to import source spreadsheet files, switch between worksheets, preview data, and receive and export result files transmitted by the output management module.

10. The automatic conversion system for cable location tables according to claim 9, characterized in that, The user interaction module is also used to provide a prompt and display a table preview area when the data parsing module cannot identify the valid data area within the first preset number of rows, so that the user can manually specify the header row through the table preview area; The system receives manually adjusted field mapping relationships from the user and, upon receiving a confirmation instruction, transmits these field mapping relationships as mapping configurations to the format recognition and field mapping module to update the preset rule base.

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