Component parameter extraction method and system and storage medium

Abstract

The invention relates to the field of data processing, and discloses a component parameter extraction method and system and a storage medium, and the method comprises the steps: loading a data manual of a target component; performing automatic retrieval on the data manual based on a preset or self-defined processing requirement, and generating a parameter index list corresponding to the type attribute of the target component; the parameter index list comprises a target parameter, a data text corresponding to the target parameter, and a position label of the data text in the data manual; and skipping to a text position and using a frame selection tool to frame and select effective parameter contents from the data text and confirming the effective parameter contents, and automatically storing the target parameter name and the effective parameter contents into a database after confirmation. According to the method and the device, the parameter searching efficiency can be improved and the accuracy of the parameter input process can be improved by presetting the component type attributes and the processing requirements, parameter-related text auxiliary retrieval and effective content secondary frame selection confirmation.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular, to a component parameter extraction method, system and storage medium. Background Art

[0002] When collating component parameters, it is necessary to identify and extract specific or relevant information from a large number of files so that it can be integrated into the subsequent workflow. For example, when receiving a new component data sheet, the key parameters need to be accurately entered into a dedicated data library. This process usually requires professionals to carefully read and understand the parameters in the data sheet, and then copy or extract them into an Excel file in a specific data format. The whole process involves a lot of repetitive manual work, which not only consumes a lot of time and energy, but may also affect the accuracy of the final data entry. Summary of the invention

[0003] In order to solve the technical problem of low efficiency in the above parameter extraction process, the present application provides a component parameter extraction method, system and storage medium, which can not only improve the efficiency of parameter search, but also improve the accuracy of parameter entry process by presetting component type attributes and processing requirements, auxiliary retrieval of parameter-related text, and secondary selection and confirmation of valid content. Specifically, the technical solution of the present application is as follows:

[0004] In a first aspect, the present application discloses a component parameter extraction method, comprising:

[0005] Load the data sheet of the target component;

[0006] Automatically search the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attribute of the target component; the parameter index list includes a target parameter, a data body corresponding to the target parameter, and a location label of the data body in the data manual;

[0007] Jump to the text position and use the selection tool to select the valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database.

[0008] In some implementations, the automatic retrieval of the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attributes of the target component comprises the following steps:

[0009] Performing word segmentation processing on the text content in the data manual;

[0010] According to the type attribute of the target component, obtaining the target parameter name;

[0011] Generate index keywords based on the target parameter name, and extract relevant data text from the text content using a machine learning algorithm;

[0012] The target parameters and the corresponding data text are marked and organized into the parameter index list.

[0013] In some embodiments, the method of jumping to the text position comprises the following steps:

[0014] Click on the target parameter, and based on the position label, the display will jump to the position page corresponding to the data text in the data manual, so as to box and confirm the valid parameter content.

[0015] In some implementations, the data body corresponding to the target parameter includes a context related to the target parameter.

[0016] In some embodiments, before automatically retrieving the data manual based on preset or customized processing requirements, the following steps are also included:

[0017] Setting the type attribute and the processing requirement of the target component;

[0018] Different type attributes correspond to different target parameters.

[0019] In some implementations, after the data sheet of the target component is loaded, the following steps are also included: determining the file format of the data sheet, performing content recognition on the graphics and text in the data sheet and converting them into an electronic text format.

[0020] In a second aspect, the present application also discloses a component parameter extraction system, comprising:

[0021] Loading module, used to load the data sheet of target components;

[0022] A retrieval module, used to automatically search the data manual based on preset or customized processing requirements, and generate a parameter index list corresponding to the type attribute of the target component; the parameter index list includes a target parameter, a data body corresponding to the target parameter, and a position label of the data body in the data manual;

[0023] A selection module is used to jump to the text position and use the selection tool to select valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database;

[0024] The storage module exists in the form of an Excel document, a relational database, or a non-relational database, and is used to store the data structure of the valid parameters and the valid parameter content selected from the data body.

[0025] In some embodiments, the component parameter extraction system further includes: a setting module, used to pre-set the type attribute and the processing requirement of the target component;

[0026] Different type attributes correspond to different target parameters.

[0027] In some embodiments, the retrieval module is specifically used to: perform word segmentation on the text content in the data manual; obtain the target parameter name according to the type attribute of the target component; generate index keywords based on the target parameter name, and use a machine learning algorithm to extract relevant data text from the text content; mark the target parameters and the corresponding data text, and organize them into the parameter index list.

[0028] In a third aspect, the present application further discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a component parameter extraction method described in any one of the above-mentioned embodiments.

[0029] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0030] 1. This application automatically extracts the parameters of components in the manual through the component parameter extraction method, which can greatly reduce the workload of manual browsing and input, and automatically retrieves the data manual based on preset or customized processing requirements. This application automatically extracts the data text related to component parameters from the data manual, and automatically stores the target parameter name and the valid parameter content into the database after selecting the valid parameter content and confirming it. It can reduce errors caused by human operation and improve the accuracy of data. It can achieve a high degree of automation in establishing databases and improve the efficiency of information management.

[0031] 2. This application uses parameter-related text auxiliary retrieval and valid content secondary box selection confirmation, which not only has a high fault tolerance rate and will not have parameter recognition errors, but also has low requirements for the model and is easy to promote. This application supports personalized configuration processing solutions by presetting component type attributes and processing requirements, and can further reduce the implementation cost of parameter extraction tools and adapt to respective types of terminals.

[0032] 3. The parameter extraction tool of this application can load and process text files of different formats and types, such as PDF, Word, PPT and image formats, etc. For file formats that cannot directly extract text content, effective parameter extraction can also be achieved by combining image processing and OCR technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The preferred implementation scheme will be described below in a clear and understandable manner with reference to the accompanying drawings to further illustrate the above-mentioned characteristics, technical features, advantages and implementation methods of the present application.

[0034] Figure 1 A flowchart of the steps of an embodiment of a method for extracting component parameters of the present application;

[0035] Figure 2 A flowchart of another embodiment of a component parameter extraction method of the present application;

[0036] Figure 3 This is a structural block diagram of an embodiment of a component parameter extraction system of the present application. DETAILED DESCRIPTION

[0037] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0038] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections.

[0039] In order to simplify the drawings, only the parts related to the invention are schematically shown in each figure, and they do not represent the actual structure of the product. In addition, in order to simplify the drawings and facilitate understanding, in some figures, only one of the parts with the same structure or function is schematically drawn or marked. In this article, "one" not only means "only one", but also means "more than one".

[0040] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0041] In a specific implementation, the terminal device described in the embodiments of the present application includes, but is not limited to, other portable devices such as mobile phones, laptop computers, tutoring machines, or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and / or touch pads). It should also be understood that in some embodiments, the terminal device is not a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., touch screen displays and / or touch pads).

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the specific implementation methods of the present application will be described below with reference to the accompanying drawings. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings and other implementation methods can be obtained based on these drawings without creative work.

[0043] Component datasheets are technical documents that describe the characteristics and parameters of electronic components in detail, usually provided by component manufacturers. The content and format vary depending on the component type and manufacturer. Datasheets are important reference materials for engineers when designing circuits and selecting components. By reading datasheets, you can fully understand the performance and characteristics of components to ensure that they meet design requirements. By analyzing the component parameters in the database, you can discover the performance characteristics and laws of different components, providing a basis for product optimization and innovation.

[0044] The existing method of extracting component parameters from component datasheets mainly relies on manual reading and understanding of documents, locking parameter information in text and pictures, and relying on the business knowledge and experience of relevant technicians to manually copy and extract relevant component parameters, and paste and input them into the corresponding rows and columns of the corresponding Excel database document.

[0045] The manual parameter extraction process has the following disadvantages and problems: The entire process is completed manually, which is inefficient. The quality of the input data varies for operators with different experience levels. Long-term boring and tedious repetitive actions can easily lead to fatigue, which greatly reduces the accuracy of the input data.

[0046] At present, although there are also automated extraction methods for searching key data and reducing manual workload, the component parameter search is different from the general text content search method. For some complex component parameters, such as parameters with special symbols and non-uniform formats, the extraction process is more complicated, and the extraction effect depends largely on the format of the input text. If the original text is ambiguous, wrong, or has irregular format, it will affect the accuracy and completeness of the extraction. When faced with some non-standard or uncommon parameter formats, the generalization ability is poor and may not be accurately recognized. In the case of poor model calculation ability, recognition errors will also occur, affecting the application of subsequent parameters.

[0047] Therefore, this application introduces technical means such as automatic extraction, automatic indexing, automatic selection, auxiliary selection and marking, and automatic storage in the database to automate most of the workflow of the component parameter extraction process, improve efficiency and accuracy; and greatly reduce the scope of manual repetitive behavior and the difficulty of operation. It lowers the threshold for using component parameter extraction tools and narrows the gap between operators with different experience levels. It can not only improve the efficiency of parameter search, but also improve the accuracy of the parameter entry process.

[0048] Reference Manual Attached Figure 1 An embodiment of a component parameter extraction method provided by the present application comprises the following steps:

[0049] S1. Load the data sheet of the target component.

[0050] S2. Automatically search the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attributes of the target components; the parameter index list includes target parameters, data text corresponding to the target parameters, and a location label of the data text in the data manual.

[0051] S3. Jump to the text position and use the selection tool to select valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database.

[0052] Specifically, the datasheet of electronic components or chips is generally in PDF, WORD or image format, and the content generally includes the following main parts: cover and basic information, including the name or model of the component, and relevant information of the manufacturer; product overview, including an introduction to the function, purpose and application scenario of the component; electrical characteristics, physical characteristics, application guide, as well as other information such as certification information and packaging information. The various parameters of the components, including electrical parameters, physical parameters, manufacturing materials, usage recommendations, etc., are generally described in the form of text, various characteristic curves, charts, etc.

[0053] The present application discloses a component parameter extraction method which is executed by a parameter extraction tool. The component datasheet is loaded into the tool to be displayed in the reader view of the tool. In one embodiment of the present application, in step S1, the data sheet of the target component is loaded; and then the following steps are included: S11, determining the file format of the data sheet. S12, performing content recognition on the graphics and text of the data sheet and converting it into an electronic text format.

[0054] Preferably, OCR (Optical Character Recognition) is used to pre-process the Datasheet before or after loading; OCR is a technology that converts text in an image into editable text. It recognizes the text content by analyzing the shape, structure, and context of the text in the image, and converts it into an electronic text format for further processing.

[0055] This application parameter extraction tool can load and process text files of different formats and types, such as PDF, Word, PPT, and image formats. For file formats that cannot directly extract text content, effective parameter extraction can also be achieved by combining image processing and OCR technology.

[0056] This application automatically extracts the parameters of components in the manual through a component parameter extraction method, which can greatly reduce the workload of manual browsing and input, and automatically retrieves the data manual based on preset or customized processing requirements. This application automatically extracts the data text related to component parameters from the data manual, and automatically stores the target parameter name and the valid parameter content into the database after selecting the valid parameter content and confirming it. It can reduce errors caused by human operations and improve the accuracy of data. It can achieve a high degree of automation in establishing databases and improve the efficiency of information management.

[0057] Another embodiment of the component parameter extraction method of the present application, based on the embodiment of the above method, the step S2 further includes the following steps:

[0058] S21, setting the type attribute and the processing requirement of the target component. Preferably, different type attributes correspond to different target parameters.

[0059] The attribute types of target components can generally be divided into: passive components, including resistors, capacitors, inductors, transformers, filters, etc.; active components, such as transistors; electrical connection components, including connectors, sockets and plugs, relays, switches, etc.; protection components, including fuses, overvoltage protection devices, overcurrent protection devices, etc.; sensor components, including temperature sensors, light sensors, pressure sensors, motion sensors, etc.; as well as power modules, display components, storage components, heat dissipation components, etc. Relevant technicians can set the level of refinement of the classification based on usage requirements. Each classification can set its own corresponding target parameters that need to be retrieved; to facilitate the management of parameter extraction tools, this application does not make specific restrictions. For example, for resistors, the target parameters that need to be retrieved are set to resistance value, rated power, accuracy, temperature coefficient, etc. For diodes, the target parameters that need to be retrieved are set to forward voltage drop, reverse breakdown voltage, maximum forward current, reverse leakage current, switching speed, etc.

[0060] The processing requirements of the target components include: parameter extraction requirements, for example, the parameters that need to be extracted for a certain component are all parameters, or the parameters that need to be extracted for a certain component are its electrical parameters; or the parameters that need to be extracted for a certain component are its physical parameters.

[0061] The processing requirements of the target components also include the requirements of automatic selection of valid parameters or manual selection of valid parameter contents. Two embodiments are provided below for illustration.

[0062] Better yet, the processing requirements of the target components can also be set as default requirements based on the usage habits of relevant technicians, so that no configuration is required when the tool is used again.

[0063] This application supports personalized configuration processing solutions by presetting component type attributes and processing requirements, and can further reduce the implementation cost of parameter extraction tools and adapt to respective types of terminals.

[0064] In other embodiments of the present application, the processing requirements of the target components also include other personalized requirements. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0065] Optionally, in one embodiment of the present application, after using a parameter extraction tool to automatically search the data manual and generate a parameter index list corresponding to the type attributes of the target component, you can choose to use automatic selection again to select valid parameter content from the data text and confirm it.

[0066] For example, using deep learning-based methods, including BERT, GPT, etc., and taking advantage of the powerful semantic understanding capabilities of pre-trained models, complex information and relationships can be extracted from the data body. Of course, other existing large models can also be used to achieve the same technical effects as this embodiment, but in order to ensure the accuracy of box selection, higher requirements are placed on the performance of the model, and the corresponding model pre-training and other processes also bring higher costs.

[0067] Optionally, in another embodiment of the present application, after using a parameter extraction tool to automatically search the data manual and generate a parameter index list corresponding to the type attributes of the target component, you can choose to select valid parameter content from the data text by manually selecting and confirming.

[0068] Reference Manual Attached Figure 2 As shown, in this embodiment, the component parameter extraction method specifically includes the following steps:

[0069] Step 1. Load the component datasheet into the tool's reader view.

[0070] Step 2: Set component type attributes and detailed processing requirements.

[0071] Step 3: Wait for the tool to complete the extraction and selection of the full-text information to form an index list.

[0072] Step 4: Locate the text based on the index.

[0073] Step 5: Automatically extract data through the content selected by the tool box, select valid content and confirm.

[0074] Step 6: The tool completes the final data storage.

[0075] Specifically, step 4 and step 5 are performed manually. The data text corresponding to the target parameter includes the context related to the target parameter. Based on the generated parameter index list, manual selection no longer requires reading a large amount of data manual text, and only requires valid parameter content judgment on a small part of the marked data text. After manual selection is confirmed, the parameters are automatically generated and stored in the specified, so that the target parameter name and the valid parameter content will be automatically stored in the database, and there is no need to perform the cumbersome step of copying and pasting. The database stores this parameter information. The same components may be used multiple times in a project. The existence of the database can avoid repeated searches and records, thereby improving work efficiency. Avoid manually searching and recording parameters from the Datasheet every time, wasting a lot of time.

[0076] This application uses parameter-related text auxiliary retrieval and secondary box selection confirmation of valid content. It not only has a high fault tolerance rate and will not have the problem of parameter recognition errors, but also has low requirements for the model and is easy to promote.

[0077] Another embodiment of a component parameter extraction method of the present application, based on the above method embodiment, step S2 is shown, automatically searching the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attribute of the target component; and also includes the following steps:

[0078] S22, performing word segmentation processing on the text content in the data manual.

[0079] Specifically, tokenization is a basic and important task in natural language processing (NLP). Its purpose is to segment continuous text strings into meaningful units, which are usually called "words" or "tokens". Tokenization is the first step in text processing and is crucial for subsequent tasks such as grammatical analysis, semantic understanding, and information retrieval.

[0080] S23. Obtain the target parameter name according to the type attribute of the target component.

[0081] Specifically, each category can set its own corresponding target parameter to be retrieved; for the convenience of managing the parameter extraction tool, this application does not make specific restrictions. For example, for capacitors, the target parameters to be retrieved are set to resistance, rated power, accuracy, temperature coefficient, etc. For diodes, the target parameters to be retrieved are set to forward voltage drop, reverse breakdown voltage, maximum forward current, reverse leakage current, switching speed, etc.

[0082] S24. Generate index keywords based on the target parameter name, and use a machine learning algorithm to extract relevant data text from the text content.

[0083] Specifically, an index keyword related to the target parameter name is generated based on the target parameter name. For example, the target component is "capacitor"; the target parameter name is: "rated voltage of capacitor"; the generated index keyword may be "rated voltage" or "rated voltage".

[0084] Preferably: in addition to using the target parameter name as the index keyword, the unit or symbol related to the parameter can also be used as the index keyword. For example, for a resistor, if the target parameter to be retrieved is set as the resistance value, the generated index keyword can be "Ω". The data text related to the target parameter can be quickly found through the index keyword.

[0085] The data body includes context related to the corresponding target parameter.

[0086] The context of the target parameter in the datasheet may include detailed notes and descriptions of the parameter, which are usually located near the parameter or in a specific part of the document. For example, a parameter may be followed by a note that says "measured at a specific temperature".

[0087] S25. Mark the target parameters and the corresponding data text, and organize them into the parameter index list.

[0088] Specifically, each target parameter may correspond to one or more data texts; the data texts are marked with special colors or symbols, and one or more data texts related to the target parameter can be displayed by clicking on the target parameter. If there are multiple data sections, the multiple data sections are sorted according to the page numbers or paragraph order in which the data appears.

[0089] Another embodiment of the method of the present application, based on any one of the above embodiments, the step S3 specifically includes: S31, clicking the target parameter, and based on the position label, causing the display to jump to the location page corresponding to the data text in the data manual, so as to box and confirm the valid parameter content.

[0090] S32. Use a selection tool to select valid parameter content from the data body and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database.

[0091] Specifically, the parameter index list includes: a location label of the data text in the data manual. By clicking on the content in the parameter index list, you can quickly jump to the location corresponding to the data text according to the location label, so as to be displayed on the display page of the parameter extraction tool.

[0092] Based on the same technical concept, the present application also discloses a component parameter extraction system, which can be used to implement any of the above-mentioned component parameter extraction methods. Specifically, an embodiment of a component parameter extraction system of the present application is shown in the attached specification. Figure 3 As shown, including:

[0093] Loading module, used to load the data sheet of the target component.

[0094] A retrieval module is used to automatically search the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attributes of the target components; the parameter index list includes the target parameters, the data text corresponding to the target parameters, and the location label of the data text in the data manual.

[0095] The box selection module is used to jump to the text position and use the box selection tool to select the valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database.

[0096] The storage module exists in the form of an Excel document, a relational database, or a non-relational database, and is used to store the data structure of the valid parameters and the valid parameter content selected from the data body. Persistent storage of data is the key to connecting to other business systems.

[0097] Specifically, the loading module loads the datasheet of the component in the tool to display it in the reader view of the tool.

[0098] In another implementation of this embodiment, the retrieval module is further used to: determine the file format of the data manual, perform content recognition on the graphics and texts in the data manual and convert them into an electronic text format.

[0099] Preferably, OCR (Optical Character Recognition) is used to pre-process the Datasheet before or after loading; OCR is a technology that converts text in an image into editable text. It recognizes the text content by analyzing the shape, structure, and context of the text in the image, and converts it into an electronic text format for further processing.

[0100] This application parameter extraction tool can load and process text files of different formats and types, such as PDF, Word, PPT, and image formats. For file formats that cannot directly extract text content, effective parameter extraction can also be achieved by combining image processing and OCR technology.

[0101] By setting the key attributes of components, the tool will automatically extract the contextual description of the relevant parameters that meet the settings from the text and mark them explicitly. The tool provides users with the function of customizing the box selection, and assists users in extracting and marking parameters through word segmentation and OCR technology. Finally, the parameters marked and confirmed by the user will be imported into the proprietary component database with one click. The whole process is completed under the reader view integrated in the tool. By automatically extracting the parameters of components in the manual through this application, the workload of manual reading and input can be greatly reduced, and the data manual can be automatically retrieved based on preset or customized processing requirements. This application automatically extracts the data text related to component parameters from the data manual, and automatically stores the target parameter name and the valid parameter content in the database after selecting the valid parameter content and confirming it. It can reduce errors caused by human operation and improve the accuracy of data. The efficiency of information management can be improved by achieving a high degree of automation in the work of establishing a database.

[0102] Another embodiment of a component parameter extraction system provided by the present application, based on the above system embodiment, the component parameter extraction system further includes: a setting module, used to pre-set the type attribute and the processing requirement of the target component;

[0103] Different type attributes correspond to different target parameters.

[0104] The attribute types of target components can generally be divided into: passive components, including resistors, capacitors, inductors, transformers, filters, etc.; active components, such as transistors; electrical connection components, including connectors, sockets and plugs, relays, switches, etc.; protection components, including fuses, overvoltage protection devices, overcurrent protection devices, etc.; sensor components, including temperature sensors, light sensors, pressure sensors, motion sensors, etc.; as well as power modules, display components, storage components, heat dissipation components, etc. Relevant technicians can set the level of refinement of the classification based on usage requirements. Each classification can set its own corresponding target parameters that need to be retrieved; to facilitate the management of parameter extraction tools, this application does not make specific restrictions. For example, for resistors, the target parameters that need to be retrieved are set to resistance value, rated power, accuracy, temperature coefficient, etc. For diodes, the target parameters that need to be retrieved are set to forward voltage drop, reverse breakdown voltage, maximum forward current, reverse leakage current, switching speed, etc.

[0105] The processing requirements of the target components include: parameter extraction requirements, for example, the parameters that need to be extracted for a certain component are all parameters, or the parameters that need to be extracted for a certain component are its electrical parameters; or the parameters that need to be extracted for a certain component are its physical parameters.

[0106] The processing requirements of the target components also include the requirements of automatic selection of valid parameters or manual selection of valid parameter contents. Two embodiments are provided below for illustration.

[0107] Better yet, the processing requirements of the target components can also be set as default requirements based on the usage habits of relevant technicians, so that no configuration is required when the tool is used again.

[0108] Another embodiment of a component parameter extraction system provided by the present application, based on the above-mentioned system embodiment, the retrieval module is specifically used to: perform word segmentation processing on the text content in the data manual; obtain the target parameter name according to the type attribute of the target component; generate index keywords based on the target parameter name, and use a machine learning algorithm to extract relevant data text from the text content; mark the target parameters and the corresponding data text, and organize them into the parameter index list.

[0109] Specifically, an index keyword related to the target parameter name is generated based on the target parameter name. For example, the target component is "capacitor"; the target parameter name is: "rated voltage of capacitor"; the generated index keyword may be "rated voltage" or "rated voltage".

[0110] Preferably: in addition to using the target parameter name as the index keyword, the unit or symbol related to the parameter can also be used as the index keyword. For example, for a resistor, if the target parameter to be retrieved is set as the resistance value, the generated index keyword can be "Ω". The data text related to the target parameter can be quickly found through the index keyword.

[0111] The data body includes context related to the corresponding target parameter.

[0112] The context of the target parameter in the datasheet may include detailed notes and descriptions of the parameter, which are usually located near the parameter or in a specific part of the document. For example, a parameter may be followed by a note that says "measured at a specific temperature".

[0113] Each target parameter may correspond to one or more data texts; the data texts are marked with special colors or symbols, and one or more data texts related to the target parameter can be displayed by clicking on the target parameter. If there are multiple data sections, the multiple data sections are sorted according to the page number or paragraph order in which the data appears.

[0114] In another implementation of this embodiment, the box selection module is further used to: click on the target parameter to make the display jump to the location page corresponding to the data text in the data manual, so as to box and confirm the valid parameter content. Specifically, the extracted context will form an index list, and the parameter index list includes: the location label of the data text in the data manual; the tool can be used to jump to the corresponding page number of the text. The whole process is completed in the reader view integrated with the tool.

[0115] Based on the same concept, the present application also discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of a component parameter extraction method described in any of the above embodiments are implemented.

[0116] The component parameter extraction method, system and storage medium of the present application have the same technical concept, and the technical details of the three embodiments are applicable to each other. In order to reduce repetition, they will not be repeated here.

[0117] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned program modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program units or modules to complete all or part of the functions described above. The program modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into a processing unit, and the above-mentioned integrated unit can be implemented in the form of hardware or in the form of software program units. In addition, the specific names of the program modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

[0118] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

Claims

1. A component parameter extraction method, characterized in that: The steps include: Load the data sheet of the target component; Automatically search the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attribute of the target component; the parameter index list includes a target parameter, a data body corresponding to the target parameter, and a location label of the data body in the data manual; Jump to the text position and use the selection tool to select the valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database.

2. A component parameter extraction method as claimed in claim 1, characterized in that: The method of automatically searching the data manual based on preset or customized processing requirements to generate a parameter index list corresponding to the type attributes of the target component comprises the following steps: Performing word segmentation processing on the text content in the data manual; According to the type attribute of the target component, obtaining the target parameter name; Generate index keywords based on the target parameter name, and extract relevant data text from the text content using a machine learning algorithm; The target parameters and the corresponding data text are marked and organized into the parameter index list.

3. A component parameter extraction method as claimed in claim 1 or 2, characterized in that: The method of jumping to the text position comprises the following steps: Click on the target parameter, and based on the position label, the display will jump to the position page corresponding to the data text in the data manual, so as to box and confirm the valid parameter content.

4. A component parameter extraction method as claimed in claim 3, characterized in that: The data body corresponding to the target parameter includes a context related to the target parameter.

5. A component parameter extraction method as claimed in claim 1, characterized in that: Before the automatic retrieval of the data manual based on the preset or customized processing requirements, the following steps are also included: Setting the type attribute and the processing requirement of the target component; Different type attributes correspond to different target parameters.

6. A component parameter extraction method according to any one of claims 1 to 5, characterized in that: The data sheet of the target component is loaded, and then further comprises the following steps: determining the file format of the data sheet, performing content recognition on the graphics and text of the data sheet and converting them into an electronic text format.

7. A component parameter extraction system, characterized in that: include: Loading module, used to load the data sheet of target components; A retrieval module, used to automatically search the data manual based on preset or customized processing requirements, and generate a parameter index list corresponding to the type attribute of the target component; the parameter index list includes a target parameter, a data body corresponding to the target parameter, and a position label of the data body in the data manual; A selection module is used to jump to the text position and use the selection tool to select valid parameter content from the data text and confirm it. After confirmation, the target parameter name and the valid parameter content are automatically stored in the database; The storage module exists in the form of an Excel document, a relational database, or a non-relational database, and is used to store the data structure of the valid parameters and the valid parameter content selected from the data body.

8. A component parameter extraction system as claimed in claim 7, characterized in that: Also includes: A setting module, used for presetting the type attribute and the processing requirement of the target component; Different type attributes correspond to different target parameters.

9. A component parameter extraction system as claimed in claim 7, characterized in that: The retrieval module is specifically used to: perform word segmentation on the text content in the data manual; obtain the target parameter name according to the type attribute of the target component; generate index keywords based on the target parameter name, and use a machine learning algorithm to extract relevant data text from the text content; mark the target parameter and the corresponding data text, and organize them into the parameter index list.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a component parameter extraction method described in any one of claims 1 to 6 are implemented.

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