Industrial detection report generation method and device, electronic equipment and storage medium

Abstract

The invention discloses an industrial detection report generation method and device, electronic equipment and a storage medium, and relates to the field of automatic report generation. The method comprises the following steps: acquiring report basic data collected by detection equipment from an industrial detection scene; analyzing the report basic data and filling the report basic data into a data field of the general data model to generate a data model object; constructing a field access hash index according to the data field in the data model object; traversing a preset template tag in the document template, and searching a target data field matched with the currently traversed target template tag in the field access hash index; and filling the target template tag with a field value corresponding to the target data field, and generating a report document based on a filling result. According to the technical scheme, the automation degree and the generation efficiency of industrial detection report generation are improved.

Description

Technical Field

[0001] This application relates to the field of information automation processing technology, and more particularly to the field of automated report generation, specifically to a method, apparatus, electronic device, and storage medium for generating industrial inspection reports. Background Technology

[0002] In industrial testing scenarios, test reports are crucial for recording test results, reflecting equipment operating status, and supporting subsequent maintenance decisions. Taking power equipment inspection as an example, testing personnel typically need to organize various data collected on-site (such as parameters like temperature, humidity, pressure, and vibration) as well as visualization results like thermal images and waveforms into test reports according to a pre-defined standard format.

[0003] Currently, report generation in most scenarios still relies on manual operation. Staff need to obtain data from the testing equipment, manually enter the report document according to a fixed format, and perform processing such as font adjustment, layout, and image insertion. This process is time-consuming and prone to errors due to human error, such as incorrect or missing data entry or inconsistent formatting. Existing automated report generation solutions are only designed for specific instruments or systems. When generating reports containing a large amount of testing data, the traditional field-by-field matching method is slow and cannot meet the needs of real-time on-site report generation.

[0004] Therefore, existing technologies still suffer from insufficient automation and low generation efficiency in the report generation process, making it difficult to meet the demand for rapid report generation in industrial testing scenarios. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for generating industrial inspection reports, so as to improve the automation and efficiency of industrial inspection report generation.

[0006] According to one aspect of this application, a method for generating an industrial testing report is provided, comprising:

[0007] Obtain the basic data for reports collected by testing equipment in industrial testing scenarios;

[0008] The report's basic data is parsed and populated into the data fields of a general data model to generate a data model object;

[0009] Construct a field access hash index based on the data fields in the data model object;

[0010] Traverse the preset template tags in the document template and search for the target data field that matches the target template tag being traversed in the field access hash index;

[0011] The target template label is populated with the field values ​​corresponding to the target data field, and a report document is generated based on the population results.

[0012] According to another aspect of this application, an apparatus for generating an industrial inspection report is provided, comprising:

[0013] The report basic data acquisition module is used to acquire the report basic data collected by testing equipment in industrial testing scenarios;

[0014] The data model object generation module is used to parse the basic data of the report and populate the data fields of the general data model to generate a data model object.

[0015] The field access index building module is used to build a field access hash index based on the data fields in the data model object;

[0016] The target data field lookup module is used to traverse the preset template tags in the document template and search for the target data field that matches the currently traversed target template tag in the field access hash index.

[0017] The report document generation module is used to populate the target template label with the field values ​​corresponding to the target data field, and generate a report document based on the population results.

[0018] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0019] At least one processor; and

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for generating an industrial inspection report according to any embodiment of this application.

[0022] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the method for generating an industrial inspection report as described in any embodiment of this application.

[0023] According to another aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements any of the industrial inspection report generation methods provided in the embodiments of this application.

[0024] The technical solution of this application embodiment automatically parses and standardizes the basic report data from different testing devices, mapping it to a general data model to achieve unified management and structured processing of testing data. Through a field access hash index built based on data fields in the data model object, it can quickly locate data fields corresponding to template tags, improving the processing efficiency of template data matching and report generation. Simultaneously, a mechanism for automatically filling data based on template tags is implemented by matching template tags with data fields, achieving automated generation of testing reports, reducing manual operations, and improving report generation efficiency. Therefore, the technical solution of this application embodiment can significantly improve the standardization, automation level, and generation efficiency of industrial testing report generation.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0026] Figure 1 This is a flowchart of a method for generating an industrial testing report according to Embodiment 1 of this application;

[0027] Figure 2 This is a flowchart of another method for generating an industrial testing report according to Embodiment 2 of this application;

[0028] Figure 3 This is a schematic diagram of the structure of an industrial testing report generation device according to Embodiment 3 of this application;

[0029] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the method for generating industrial inspection reports according to embodiments of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart of a method for generating an industrial inspection report according to Embodiment 1 of this application. This embodiment is applicable to scenarios where reports are automatically generated from data collected by inspection equipment in industrial inspection settings. This method can be executed by an industrial inspection report generation device, which can be implemented in hardware and / or software and can be configured in a computer device. Figure 1 As shown, the method includes:

[0034] S101. Obtain the basic data for reports collected by testing equipment from industrial testing scenarios.

[0035] In this embodiment, the industrial inspection scenario refers to the application environment in which the operating status, performance parameters, or environmental parameters of the inspected object are collected and analyzed by inspection equipment during industrial production or equipment operation. The inspection equipment includes, but is not limited to, infrared thermal imagers, vibration sensors, pressure sensors, humidity sensors, temperature sensors, or other inspection instruments capable of collecting equipment status parameters; the inspected object includes, but is not limited to, power equipment, mechanical equipment, or production line devices. The basic data for the report refers to structured or semi-structured data collected by the inspection equipment and preprocessed, including inspection parameter data and visualization data. Inspection parameter data includes, but is not limited to, temperature, humidity, pressure, or inspection time; visualization data includes, but is not limited to, thermal images, waveform graphs, or trend charts.

[0036] Specifically, in industrial testing scenarios, acquiring the basic data collected by testing equipment provides a reliable data basis for subsequent report generation and analysis. This reduces manual data collection and entry, improves data processing efficiency and accuracy, and provides a data source for the rapid generation and automated processing of industrial testing reports.

[0037] S102. Parse the basic data of the report and populate the data fields of the general data model to generate a data model object.

[0038] In this embodiment, the general data model refers to an abstract data structure used to uniformly represent various types of data collected during industrial testing. Its design is adaptable to testing data from different sources and in different formats. The general data model contains multiple predefined data fields. A data model object is a specific instance generated after parsing the report's basic data and populating it into the fields of the general data model. For example, each data model object corresponds to a dataset from a single test, encapsulating the actual numerical values, images, or other acquisition results, and can be accessed, matched, and manipulated as an independent entity during report generation.

[0039] Specifically, by parsing and structuring the collected basic data for reports, it is populated into a unified, general-purpose data model, thereby generating a data model object for efficient representation and management of data from each test. This approach not only enables rapid processing and unified storage of data from different sources and formats, but also provides a reliable data foundation for subsequent template matching and report generation. This significantly improves the automation and efficiency of report generation, and reduces the risk of errors caused by non-standard data processing or manual operation.

[0040] S103. Construct a field access hash index based on the data fields in the data model object.

[0041] In this embodiment, the field access hash index refers to an efficient retrieval structure built based on the data fields in the data model object. By mapping each data field to a unique index value, the required data fields can be quickly located and accessed when generating the report. Specifically, by constructing a field access hash index on the data fields in the data model object, rapid location and efficient access to each field are achieved, thereby accelerating the data field lookup speed. This method can significantly improve processing efficiency when generating reports containing a large number of inspection points or complex data, reduce delays in field-by-field retrieval and data filling processes, and thus improve the automation level and efficiency of industrial inspection report generation.

[0042] S104. Traverse the preset template tags in the document template and search for the target data field that matches the target template tag being traversed in the field access hash index.

[0043] In this embodiment, a document template refers to a standardized file structure used to generate industrial testing reports, in which data placeholders and format specifications are pre-designed. For example, the document template can support multiple report formats and styles, facilitating the automatic generation of standard-compliant report documents based on testing data, ensuring content completeness, consistent layout, and reusability for different testing tasks or data generation scenarios using different testing equipment. Template tags are pre-defined placeholders in the document template, used to indicate the specific data field locations to be filled. The target template location refers to the position of the template tag in the currently traversed document template, used to indicate the specific location where data needs to be filled. The target data field refers to the data field in the general data model corresponding to the target template tag, i.e., the field storing actual testing data or visualization results.

[0044] Specifically, by traversing the preset template tags in the document template and quickly searching the field access hash index for the target data field that matches the currently traversed target template tag, efficient data-template matching is achieved. This method can automatically complete the matching operation of a large number of data fields, significantly improving the processing speed and automation level of report generation, and providing reliable support for generating high-quality, uniformly formatted industrial testing reports.

[0045] S105. Fill the target template label with the field values ​​corresponding to the target data field, and generate a report document based on the filling results.

[0046] Specifically, by automatically filling the actual values ​​of target data fields into the corresponding target template tags and generating a complete report document based on the filling results, the system achieves automated conversion from data to document. This method can quickly organize and format large amounts of testing data, significantly improving report generation efficiency and automation, while ensuring the accuracy and format consistency of the report content. It also reduces the risk of errors caused by manual operation, providing an efficient and reliable report generation method for industrial testing.

[0047] The technical solution of this application embodiment automatically parses and standardizes the basic report data from different testing devices, mapping it to a general data model to achieve unified management and structured processing of testing data. Through a field access hash index built based on data fields in the data model object, it can quickly locate data fields corresponding to template tags, improving the processing efficiency of template data matching and report generation. Simultaneously, a mechanism for automatically filling data based on template tags is implemented by matching template tags with data fields, achieving automated generation of testing reports, reducing manual operations, and improving report generation efficiency. Therefore, the technical solution of this application embodiment can significantly improve the standardization, automation level, and generation efficiency of industrial testing report generation.

[0048] Example 2

[0049] Figure 2 This is a flowchart of another method for generating an industrial testing report according to Embodiment 2 of this application. The technical solution of this embodiment further defines the process of parsing the basic data of the report based on the technical solutions of the above embodiments. For example... Figure 2 As shown, the method includes:

[0050] S201. Obtain the basic data for reports collected by testing equipment from industrial testing scenarios.

[0051] S202. Based on the relationship between candidate data sources and candidate parsing logic, determine the target data source to which the basic data of the report belongs from the candidate data sources, and determine the target parsing logic associated with the target data source.

[0052] S203. Using target parsing logic, the basic data of the report is parsed and populated into the data fields of the general data model to generate a data model object.

[0053] In this embodiment, candidate data sources refer to multiple available raw data sources, each corresponding to a different detection device, file, or interface, used to provide the basic data for the report. Candidate parsing logic refers to the methods or algorithms used to process data from each candidate data source, including operations such as data parsing, field mapping, and format conversion. Target data source refers to the specific data source among the candidate data sources that corresponds to the current basic data for the report. Target parsing logic refers to the parsing methods or algorithms matched to the target data source, used to correctly parse the basic data for the report and populate it into the general data model.

[0054] Specifically, by establishing the relationship between candidate data sources and candidate parsing logic, the target data source to which the current report's basic data belongs is determined. Then, the parsing logic matching this target data source is identified. This parsing logic is used to process the report's basic data, structuring the data and populating it into a unified data model to generate data model objects. This enables automated parsing and standardized storage of data from different sources and formats. This method ensures a high degree of matching between data sources and parsing methods, improving the accuracy and consistency of data processing, while significantly enhancing the efficiency and automation of report generation.

[0055] S204. Construct a field access hash index based on the data fields in the data model object.

[0056] For example, the process of constructing a field access hash index can be to convert each data field in the data model object into a key-value pair format, where the index key is used to identify the field path, and the index value consists of the field content, field type, and field attributes. For example, the task name field: index key is "Task_TaskName", content is "20250925-Inspection of Cabinet No. 1", index value type is DateTime, attribute is {"Format":"yyyy-MM-dd"}; the task status field: index key is "Task_State", index value content is "Inspection in Progress", type is string, attribute is {}; the task trend chart field: key is "Task_ThermalChartPath", content is "C: / images / chart.jpg", type is string, attribute is {}; the task item list field: index key is "Task_ItemList", index value content is List. <taskitem>The type is List <taskitem>The attribute is {"IsList":"True"}. Using this method, a fast-access index can be created for each field in the data model object, significantly improving the retrieval efficiency of subsequent field matching and template filling.

[0057] S205. Traverse the preset template tags in the document template and search for the target data field that matches the target template tag being traversed in the field access hash index.

[0058] S206. Fill the target template label with the field values ​​corresponding to the target data field, and generate a report document based on the filling results.

[0059] The technical solution of this application further defines the parsing process of the basic data of the report based on the above-mentioned technical solutions. By providing multiple data sources and data source parsing logic, the target data source and target parsing logic corresponding to the basic data of the report are determined. The parsing logic is used to parse the data and populate it into a general data model, thereby flexibly adapting to multiple candidate data sources and parsing methods, effectively dealing with basic data of the report in different data formats, achieving high compatibility and automation of report generation, and providing a reliable and highly adaptable efficient report generation method for industrial testing.

[0060] In an optional implementation, the method further includes: when the reporting base data belongs to a new data source other than the candidate data source, constructing new parsing logic adapted to the new data source based on the new data source; and adding the new data source and the new parsing logic to the candidate data source and the candidate parsing logic, respectively.

[0061] Specifically, when a new data source is identified as the basis for the report, in addition to existing candidate data sources, a new, adapted parsing logic is constructed based on this new data source. The new data source and its parsing logic are then added to the candidate data source and candidate parsing logic sets, respectively, enabling rapid adaptation and processing of new or heterogeneous data sources. This approach ensures dynamic expansion to support data from different sources and formats, while significantly improving the compatibility and flexibility of the report generation process. This allows industrial testing to maintain efficient and reliable automated report generation capabilities in the face of diverse data environments.

[0062] In an optional implementation, the method further includes: in response to a newly added template tag in the document template, adding a corresponding new data field in a preset general data model based on the newly added template tag.

[0063] Specifically, for newly added template tags in the document template, corresponding new data fields are added to the preset general data model, ensuring that the location of the new template tag can be correctly mapped to the data field in the data model. This method can quickly adapt to changes in the template structure, enabling dynamic expansion of the general data model and template tags. It can also cope with constantly changing report formats and business needs, maintaining efficient and automated data population and report generation capabilities.

[0064] In one optional implementation, traversing the preset template tags in the document template and searching for the target data field that matches the currently traversed target template tag in the field access hash index includes: traversing the preset template tags in the document template according to the tag index table and searching for the target data field that matches the currently traversed target template tag in the field access hash index; wherein, the tag index table obtains tag classification results by classifying all preset tags according to preset tag types; wherein, the preset tag types include at least one of basic data tags, image data tags, or batch data tags; extracting the tag name and tag type corresponding to the preset tags according to the tag classification results and constructing the tag index table.

[0065] In this embodiment, the tag index table refers to an index structure that categorizes all preset template tags in the document template according to their types. This structure guides traversal and facilitates quick retrieval of target data fields. Specifically, by classifying all preset template tags in the document template according to their tag types, the corresponding tag names and types are extracted to construct a tag index table. The template tags in the document template are then traversed according to this tag index table. The target data field matching the currently traversed target template tag is quickly found in the field access hash index, achieving efficient data-template correspondence. This method significantly improves matching efficiency when generating reports containing a large number of preset template tags, thereby increasing the report generation speed.

[0066] In one optional implementation, filling the target template tag with the field value corresponding to the target data field includes: if the target template tag is a basic data tag, then filling the target template tag with the field value corresponding to the target data field; if the target template tag is an image data tag, then determining the target image path according to the field value corresponding to the target data field, and filling the image object corresponding to the image path into the target template tag; if the target template tag is a batch data tag, then filling the field value into the target template tag containing the loop start identifier and the field identifier in sequence according to the field value corresponding to the target data field.

[0067] The loop start identifier is used to indicate the starting position for filling field values; the field identifier is used to indicate the corresponding position of the field value in the template other than the starting position.

[0068] In this embodiment, basic data tags refer to template tags in the document template used to populate basic data such as single text, numbers, or dates. Image data tags refer to template tags in the template used to populate image objects. Batch data tags refer to loop tags in the template used to populate multiple data records, supporting the sequential population of a set of field values ​​into multiple positions in the template.

[0069] Specifically, different data filling methods are adopted for different types of template tags. For basic data tags, the field values ​​corresponding to the target data fields are directly filled into the target template tag positions. For image data tags, the image path is determined based on the field values ​​corresponding to the target data fields, and the corresponding image objects are filled into the target template tag positions. For batch data tags, the field values ​​corresponding to the target data fields are sequentially filled into the target template tag positions containing loop start identifiers and field identifiers in the template to ensure that multiple data records can be correctly arranged and displayed. The above method achieves flexible matching between template types and data filling methods, and can automatically handle multiple data types such as text, numbers, and images, effectively improving the efficiency and accuracy of batch data filling, thereby ensuring the completeness and efficiency of report generation.

[0070] For example, when traversing the preset template tags in the document template and searching for a target data field that matches the currently traversed target template tag in the field access hash index, if no matching target data field is found for the currently traversed target template tag, the target template tag is marked as missing data, and a preset placeholder is filled in the target template tag position. By marking cases where no matching target data field is found during template tag traversal and filling the corresponding position with a preset placeholder, data missing issues can be automatically identified and handled during report generation, avoiding blanks, misalignments, or abnormal formatting in the report. The above method not only ensures the integrity of the overall report structure and the stability of the layout, but also provides intuitive prompts for subsequent data verification and manual review, enabling inspection personnel to quickly locate the source of missing data.

[0071] Example 3

[0072] Figure 3 This is a schematic diagram of an industrial testing report generation device according to Embodiment 3 of this application. This embodiment is applicable to scenarios where reports are automatically generated from data collected by testing equipment in industrial testing scenarios. The industrial testing report generation device can be implemented in hardware and / or software, and can be configured in a computer device. Figure 3 As shown, the industrial test report generation device 300 includes:

[0073] The report basic data acquisition module 310 is used to acquire the report basic data collected by the testing equipment in the industrial testing scenario;

[0074] The data model object generation module 320 is used to parse the basic data of the report and fill it into the data fields of the general data model to generate a data model object.

[0075] The field access index building module 330 is used to build a field access hash index based on the data fields in the data model object;

[0076] The target data field lookup module 340 is used to traverse the preset template tags in the document template and search for the target data field that matches the currently traversed target template tag in the field access hash index.

[0077] The report document generation module 350 is used to fill the target template label with the field value corresponding to the target data field, and generate a report document based on the filling result.

[0078] In one optional implementation, the data model object generation module 320 is specifically used for:

[0079] Based on the relationship between candidate data sources and candidate parsing logic, the target data source to which the basic data of the report belongs is determined from the candidate data sources, and the target parsing logic associated with the target data source is determined;

[0080] Using the target parsing logic, the basic data of the report is parsed and populated into the data fields of the general data model to generate a data model object.

[0081] In an optional implementation, the data model object generation module 320 further includes a new data source processing module, which is specifically used for:

[0082] When the basic data of the report belongs to a new data source other than the candidate data source, a new parsing logic adapted to the new data source is constructed based on the new data source.

[0083] Add the new data source and the new parsing logic to the candidate data source and candidate parsing logic, respectively.

[0084] In an optional embodiment, the industrial testing report generation device 300 further includes a new template label processing module, which is specifically used for:

[0085] In response to a newly added template tag in the document template, a corresponding new data field is added to the preset general data model based on the newly added template tag.

[0086] In one optional implementation, the target data field lookup module 340 is specifically used for:

[0087] The document template is traversed according to the tag index table, and the target data field that matches the target template tag being traversed is searched in the field access hash index.

[0088] The tag index table obtains tag classification results by classifying all preset tags according to preset tag types; wherein the preset tag types include at least one of basic data tags, image data tags, or batch data tags; and the tag names and tag types corresponding to the preset tags are extracted based on the tag classification results to construct the tag index table.

[0089] In one optional implementation, the report document generation module 350 is specifically used for:

[0090] If the target template tag is a basic data tag, then the target template tag is filled with the field value corresponding to the target data field;

[0091] If the target template tag is an image data tag, then the target image path is determined according to the field value corresponding to the target data field, and the image object corresponding to the image path is filled into the target template tag;

[0092] If the target template label is a batch data label, then according to the field value corresponding to the target data field, the field value is sequentially filled into the target template label containing the loop start identifier and the field identifier; wherein, the loop start identifier is used to indicate the starting position of the field value filling; the field identifier is used to indicate the corresponding position of the field value in the template other than the starting position.

[0093] The industrial testing report generation apparatus provided in this application embodiment can execute the industrial testing report generation method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method.

[0094] This application also provides an electronic device, a readable storage medium, and a computer program product. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for generating any industrial testing report according to this application.

[0095] Example 4

[0096] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the method for generating industrial inspection reports according to embodiments of this application. Figure 4 A schematic diagram of an electronic device 410 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0097] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0098] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0099] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as methods for generating industrial inspection reports.

[0100] In some embodiments, the method for generating an industrial inspection report may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the method for generating an industrial inspection report described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the method for generating an industrial inspection report by any other suitable means (e.g., by means of firmware).

[0101] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0102] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0103] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0104] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0105] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0106] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0107] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0108] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.< / taskitem> < / taskitem>

Claims

1. A method for generating an industrial inspection report, characterized by, include: Obtain the basic data for reports collected by testing equipment in industrial testing scenarios; The report's basic data is parsed and populated into the data fields of a general data model to generate a data model object; Construct a field access hash index based on the data fields in the data model object; Traverse the preset template tags in the document template and search for the target data field that matches the target template tag being traversed in the field access hash index; The target template label is populated with the field values ​​corresponding to the target data field, and a report document is generated based on the population results.

2. The method of claim 1, wherein, The step of parsing the basic data of the report and populating it into the data fields of the general data model to generate a data model object includes: Based on the relationship between candidate data sources and candidate parsing logic, the target data source to which the basic data of the report belongs is determined from the candidate data sources, and the target parsing logic associated with the target data source is determined; Using the target parsing logic, the basic data of the report is parsed and populated into the data fields of the general data model to generate a data model object.

3. The method according to claim 2, characterized in that, The method further includes: When the basic data of the report belongs to a new data source other than the candidate data source, a new parsing logic adapted to the new data source is constructed based on the new data source. Add the new data source and the new parsing logic to the candidate data source and candidate parsing logic, respectively.

4. The method according to claim 1, characterized in that, The method further includes: In response to a newly added template tag in the document template, a corresponding new data field is added to the preset general data model based on the newly added template tag.

5. The method according to claim 1, characterized in that, The process involves traversing preset template tags in the document template and searching for target data fields in the field access hash index that match the target template tag being traversed, including: The document template is traversed according to the tag index table, and the target data field that matches the target template tag being traversed is searched in the field access hash index. The tag index table obtains tag classification results by classifying all preset tags according to preset tag types; wherein the preset tag types include at least one of basic data tags, image data tags, or batch data tags; and the tag names and tag types corresponding to the preset tags are extracted based on the tag classification results to construct the tag index table.

6. The method according to claim 1, characterized in that, The step of filling the target template tag with the field value corresponding to the target data field includes: If the target template tag is a basic data tag, then the target template tag is filled with the field value corresponding to the target data field; If the target template tag is an image data tag, then the target image path is determined according to the field value corresponding to the target data field, and the image object corresponding to the image path is filled into the target template tag; If the target template label is a batch data label, then according to the field value corresponding to the target data field, the field value is sequentially filled into the target template label containing the loop start identifier and the field identifier; wherein, the loop start identifier is used to indicate the starting position of the field value filling; the field identifier is used to indicate the corresponding position of the field value in the template other than the starting position.

7. An apparatus for generating industrial testing reports, characterized in that, include: The report basic data acquisition module is used to acquire the report basic data collected by testing equipment in industrial testing scenarios; The data model object generation module is used to parse the basic data of the report and populate the data fields of the general data model to generate a data model object. The field access index building module is used to build a field access hash index based on the data fields in the data model object; The target data field lookup module is used to traverse the preset template tags in the document template and search for the target data field that matches the currently traversed target template tag in the field access hash index. The report document generation module is used to populate the target template label with the field values ​​corresponding to the target data field, and generate a report document based on the population results.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for generating an industrial inspection report according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for generating an industrial inspection report as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method for generating an industrial inspection report according to any one of claims 1-6.

Images