Automatic DB conversion of railway equipment precision diagnostic data and AI-based automatic photo album generation system

Abstract

The present invention relates to an automatic database creation of precision diagnostic data for railway facilities and an AI-based automatic photo album generation system. The present invention relates to a system (100) for automatic database creation of precision diagnostic data for railway facilities and automatic generation of photo albums based on AI, comprising: an integrated basic data database creation module (110) that receives photos, handwritten data, and basic measurement values ​​(Raw Data) from a field smart terminal, and maps and stores them in a relational database (RDBMS) by combining the use of public data APIs and the history of facility aging; an attribute diagnostic-based environmental correction type comprehensive grade calculation engine (120) that dynamically sets threshold values ​​and weights for each site through a variable diagnostic template engine, and automatically determines an overall performance grade of A to E by reflecting environmental correction coefficients in safety, durability, and usability scores; an AI multimodal photo and measurement type classifier (130) that identifies facility objects, defect states, and environmental risk factors from collected images and automatically classifies and stores them by combining them with measurement type tags; and a one-click report and photo album generator (140) that automatically maps the comprehensive grade data and photos by automatically classified measurement type to a statutory report template to generate a document for distribution with one click. The present invention, configured as described above, relates to a system for automatically creating a database of precision diagnostic data based on railway safety laws and regulations and precision diagnosis and performance evaluation protocols for railway facilities, calculating overall performance grades, and automatically generating AI photo albums by measurement type. By doing so, the quality and reliability of the system product are significantly improved, thereby enabling workers to have a positive impression.

Description

Technology Field

[0001] An embodiment of the present invention relates to an automatic database of precision diagnostic data for railway facilities and an AI-based automatic photo album generation system. More specifically, it relates to an automatic database of precision diagnostic data based on railway safety laws and regulations and precision diagnostic and performance evaluation protocols for railway facilities, a system for calculating overall performance grades, and an AI-based automatic photo album generation system by measurement type. This significantly improves the quality and reliability of the system product, thereby enabling workers to have a positive impression. Background Technology

[0003] Unless otherwise indicated in this specification, the contents described in this identification item are not prior art for the claims of this application, and are not recognized as prior art simply because they are described in this identification item.

[0004] As is well known, the precision diagnosis and performance evaluation of railway facilities must go beyond a simple suitability or non-suitability judgment and conduct a comprehensive evaluation based on multifaceted indicators such as safety, durability, and usability.

[0005] However, the above conventional method of work had the following problems.

[0006] First, because basic maintenance data collected on-site and environmental factor data (e.g., pollution, salt damage) from external agencies such as the Korea Meteorological Administration were not automatically linked, it was difficult to accurately reflect the impact of environmental stress on equipment performance degradation in the comprehensive evaluation.

[0007] Second, in the process of calculating safety, durability, and usability ratings based on collected data, the manual application of complex weights and environmental correction factors to tens of thousands of facilities resulted in frequent human errors and was time-consuming.

[0008] Third, when organizing field photos or supporting photos, which serve as key evidence for the diagnostic report, the classification based on the purpose of shooting or measurement type (e.g., insulation resistance measurement, crack depth measurement, etc.) was performed manually, severely reducing the efficiency of report preparation.

[0010] In order to solve the aforementioned problems, the following prior art documents were developed in the past; however, a major problem still arose in that the problems of the aforementioned prior art could not be solved all at once. Prior art literature

[0012] Korean Registered Patent Publication No. 2841019 (July 28, 2025) has been registered. Korean Registered Patent Publication No. 2870142 (October 2, 2025) has been registered. Korean Registered Patent Publication No. 2870144 (October 2, 2025) has been registered. Korean Registered Patent Publication No. 2870125 (October 2, 2025) has been registered. Korean Registered Patent Publication No. 2870134 (October 2, 2025) has been registered. The problem to be solved

[0013] The present invention has been devised to resolve the various problems of the prior art described above. Its first objective is to provide a system for the automatic database creation of precision diagnostic data for railway facilities and the automatic generation of AI-based photo albums, equipped with an integrated basic data database creation module, an attribute diagnosis-based environment-corrected comprehensive grade calculation engine, an AI multimodal photo and measurement type classifier, and a one-click report and photo album generator. The second objective of the present invention, based on the technical configuration described above, is to provide a system for the automatic database creation of precision diagnostic data based on railway safety laws and regulations and precision diagnosis and performance evaluation protocols for railway facilities, comprehensive performance grade calculation, and AI automatic photo album generation by measurement type. The third objective is to create an integrated database (DB) of basic measurement data (Raw Data), various equipment measurement data, maintenance data, handwritten records, and field photos collected on-site in accordance with railway safety laws and regulations and precision diagnosis and performance evaluation protocols, and to automatically determine the final comprehensive evaluation grade by reflecting the history of equipment aging and surrounding environmental factors (e.g., pollution, salt damage, etc.) as correction factors when calculating safety, durability, and usability indices based on this database. The fourth objective is to provide a system that derives results and ultimately generates a statutory report from the Korea Transportation Safety Authority (Evaluation Regulations for Precision Diagnosis Performance Evaluation Result Reports) with a single click, including an album of supporting photographs classified by measurement type (e.g., electrical measurement, degradation test, corrosion inspection, etc.); the fifth objective is to prevent data loss by automatically creating a database of basic data in accordance with regulations and to establish a preventive maintenance system through long-term equipment history tracking; the fifth objective is to ensure data reliability and drastically shorten the report approval process by automating complex grade calculation and comprehensive evaluation processes; and the sixth objective is to provide an environment where engineers can focus on technical judgment by reducing simple, repetitive administrative tasks by more than 90% through the automatic classification of photos by measurement type using AI.The seventh objective is to provide an automated database of precision diagnostic data for railway equipment and an AI-based automatic photo album generation system that significantly improves the quality and reliability of system products, thereby creating a positive image for workers. means of solving the problem

[0015] To achieve this objective, the present invention relates to an automatic database creation of precision diagnostic data for railway facilities and an AI-based automatic photo album generation system, comprising: an integrated raw data database creation module that receives photos, handwritten data, and raw measurement values ​​from field smart terminals, and maps and stores them in a relational database (RDBMS) by combining the use of public data APIs and equipment aging history; an attribute diagnostic-based environmental correction type comprehensive grade calculation engine that dynamically sets site-specific thresholds and weights through a variable diagnostic template engine and automatically determines an overall performance grade from A to E by reflecting environmental correction coefficients in safety, durability, and usability scores; an AI multimodal photo and measurement type classifier that identifies equipment objects, defect states, and environmental risk factors from collected images and automatically classifies and stores them by combining them with measurement type tags; and a one-click report and photo album generator that automatically maps comprehensive grade data and photos by automatically classified measurement type to a statutory report template to generate a document for distribution with a single click. Effects of the invention

[0017] As described in detail above, the present invention relates to a system for automatically creating a database of precision diagnosis data based on railway safety laws and regulations and precision diagnosis and performance evaluation protocols for railway facilities, calculating a comprehensive performance grade, and automatically generating an AI photo album by measurement type.

[0018] In particular, the present invention provides a system that integrates raw data, various equipment measurement data, maintenance data, handwritten records, and field photos collected at the site in accordance with railway safety laws and regulations and precision diagnosis and performance evaluation protocols into a database (DB), automatically derives a final comprehensive evaluation grade by reflecting the history of equipment aging and surrounding environmental factors (e.g., pollution, salt damage, etc.) as correction factors when calculating safety, durability, and usability indices based on the data, and finally generates a statutory report with one click that includes a photo album of evidence classified by measurement type (e.g., electrical measurement, deterioration test, corrosion inspection, etc.).

[0019] In addition, the present invention prevents data loss by automatically converting basic data into a database according to the protocol, and establishes a preventive maintenance system through long-term tracking of equipment history.

[0020] In addition, the present invention automates the complex grade calculation and comprehensive evaluation processes to ensure data reliability and drastically shorten the report approval process.

[0021] In addition, the present invention provides an environment that reduces simple, repetitive administrative tasks for engineers by more than 90% and allows them to focus on technical judgments through automatic classification of photos by measurement type using AI.

[0022] This invention is a very useful invention that, due to the aforementioned effects, significantly improves the quality and reliability of system products and enables workers to develop a positive image.

[0024] Hereinafter, a preferred embodiment of the present invention for achieving these effects will be described in detail with reference to the attached drawings. Brief explanation of the drawing

[0026] FIG. 1 shows the automatic database conversion of railway equipment precision diagnostic data and AI-based application of the present invention. Block diagram of an automatic photo album generation system. FIG. 2 shows the automatic database conversion of railway equipment precision diagnostic data and AI-based application of the present invention. Flowchart of the automatic photo album generation system. Specific details for implementing the invention

[0027] The automatic database conversion of railway equipment precision diagnosis data and the AI-based automatic photo album generation system applied in the present invention are configured as shown in FIGS. 1 and 2.

[0028] In the following description of the present invention, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the present invention, such detailed description will be omitted.

[0029] Furthermore, the terms described below are established considering their functions in the present invention, and since these may vary depending on the producer's intent or practice, their definitions should be based on the content throughout this specification.

[0030] In addition, the size and thickness of each component shown in the drawings are depicted arbitrarily for convenience of explanation, so the present invention is not necessarily limited to what is shown in the drawings.

[0031] First, the present invention relates to an automatic DB of railway equipment precision diagnostic data and an AI-based automatic photo album generation system (100), and is configured as follows.

[0032] That is, the present invention is equipped with an integrated basic data DB module (110) that receives photos, handwritten data, and basic measurement values ​​(Raw Data) of a railway facility site from a field smart terminal, and combines the use of public data APIs (e.g., Korea Meteorological Administration, etc.) and the history of facility aging to map and store them in a relational database (RDBMS).

[0033] In addition, the present invention is equipped with an attribute diagnosis-based environmental correction type comprehensive grade calculation engine (120) that dynamically sets site-specific thresholds and weights through a variable diagnostic template engine, automatically determines an overall performance grade of A to E by reflecting environmental correction coefficients in safety, durability, and usability scores, and dynamically maps a pre-set weight matrix based on the protocol of the railway facility site to calculate environmental correction coefficients for each pre-defined environmental stress item in the algorithm result value.

[0034] At this time, the attribute diagnosis-based environment correction type comprehensive grade calculation engine (120) extracts past inspection history and current environment, aging, failure and malfunction history data of a specific facility from a stored database, and dynamically sets different measurement specifications and threshold values ​​for each site through a variable diagnostic template engine, and automatically determines a comprehensive performance grade that reflects safety, durability, usability scores and environment correction coefficients according to the protocol by comparing and analyzing the information of the pre-set 'attribute diagnosis standard database' with the field measurement values.

[0035] In addition, the above-mentioned attribute diagnosis-based environment-corrected comprehensive grade calculation engine (120) dynamically sets threshold values ​​and weights for each item through a variable diagnosis template engine to respond to variations in basic data items and measurement specifications defined differently for each railway site service, corrects durability based on the installation period and accumulated environmental stress of the equipment, weights usability evaluation based on past failure data and current environmental severity by linking with a failure history database, converts basic data items such as electrical measurements, wear rate, corrosion level, and crack depth collected at the site into numerical grade elements according to precision diagnosis and performance evaluation criteria and applies them, and finally calculates a comprehensive grade between A and E that integrates the performance factors and external environmental risks of the equipment.

[0036] The present invention is equipped with an AI multimodal photo and measurement type classifier (130) that identifies equipment objects, defect conditions, and environmental risk factors in collected images, automatically classifies and stores them by combining them with measurement type tags (e.g., deterioration / corrosion / wear / cracks, etc.), and extracts image feature vectors from field photo data to automatically perform tagging according to predefined equipment object types, deterioration conditions, and measurement type mapping rules.

[0037] In addition, the present invention is equipped with a one-click report and photo album generator (140) that automatically maps comprehensive grade data and photos of automatically classified measurement types to a legal report template to generate a distribution document (PDF / HWP) with one click.

[0038] Meanwhile, the integrated basic data DB module (110) applied to the present invention is equipped with the following technical configuration.

[0039] That is, the present invention is equipped with a field smart terminal (111) that transmits photo / handwriting / measurement Raw Data to a collection server (113).

[0040] In addition, the present invention is equipped with a public data API (112) that automatically receives data on pollution, salt damage, and weather environmental factors of the relevant area shared by an external agency (e.g., the Korea Meteorological Administration) through a public data API or web scraping.

[0041] At this time, the above-mentioned public data API (112) applied to the present invention reduces the process of manual input and stably provides the basis data required for environmental correction.

[0042] In addition, the present invention is equipped with a collection server (113) that is connected to the field smart terminal (111) and the public data API (112), receives photos, handwritten notes, and measurement values ​​uploaded from the field, transmits them to a storage / processing pipeline, and reduces data omissions and duplications while collecting them in a standard format.

[0043] In addition, the present invention is provided with an integrated precision diagnosis and environmental DB (114) that processes data from the collection server (113) and stores field inspection data (e.g., measurements, manual records, photos, etc.), environmental data, and equipment history in one place based on the equipment ID.

[0044] In addition, the attribute diagnosis-based environment correction type comprehensive grade calculation engine (120) applied to the present invention is equipped with the following technical configuration.

[0045] That is, the present invention is equipped with a variable diagnostic and comprehensive evaluation engine (121) that dynamically sets items, thresholds, and weights by reflecting different protocols for each site / service, calculates inspection data based on this, and automatically performs a comprehensive grade calculation logic.

[0046] In addition, the present invention is equipped with a safety / durability / practicality comprehensive evaluation and environmental correction coefficient (122) that calculates safety, durability, and usability (practicality) scores after performing the algorithm of the variable diagnosis and comprehensive evaluation engine (121), and then applies a correction coefficient according to environmental stress such as pollution and salt damage to objectively determine the final A~E comprehensive grade.

[0047] In addition, the AI ​​multimodal photo / measurement type classifier (130) applied to the present invention is equipped with the following technical configuration.

[0048] That is, the present invention is equipped with an AI measurement type recognition / classification (131) that analyzes metadata regarding a photograph and a preset photograph type setting to automatically determine what equipment / condition the photograph is and what measurement type (e.g., electrical, corrosion, crack, etc.) evidence it is.

[0049] At this time, the AI ​​measurement type recognition / classification (131) reduces the time a person spends classifying photos one by one.

[0050] In addition, the present invention is connected to the AI ​​measurement type recognition / classification (131) and is equipped with automatic tagging & folderging (132) that attaches measurement type, equipment, section, and date information determined by the AI ​​as tags and automatically organizes them into a folder / album structure according to the criteria.

[0051] At this time, the above automatic tagging & folderting (132) creates a bundle that can be used immediately for inserting reports.

[0052] Furthermore, the one-click report and photo album generator (140) applied to the present invention is configured to dynamically configure the layout of the photo album and automatically enter descriptions by combining one or more of the criteria for each shooting date, each track section / station, each equipment type, and each measurement type according to the user's selection.

[0054] Meanwhile, the present invention can be modified in various ways and can take various forms when applying the above-mentioned components.

[0055] And it should be understood that the present invention is not limited to the specific form mentioned in the above detailed description, but rather should be understood to include all variations, equivalents, and substitutions within the spirit and scope of the invention as defined by the appended claims.

[0057] The effects of the railway equipment precision diagnosis data automatic DB conversion and AI-based photo album automatic generation system of the present invention, configured as described above, are as follows.

[0058] First of all, the present invention relates to a system for automatically creating a database of precision diagnosis data based on railway safety laws and regulations and precision diagnosis and performance evaluation protocols for railway facilities, calculating a comprehensive performance grade, and automatically generating an AI photo album by measurement type.

[0059] To this end, FIG. 1 applied to the present invention is a block diagram of the automatic DB conversion of railway equipment precision diagnosis data and AI-based automatic photo album generation system applied to the present invention, showing how the integrated basic data DB conversion module (110), the attribute diagnosis-based environment correction type comprehensive grade calculation engine (120), the AI ​​multimodal photo / measurement type classifier (130), and the one-click report and photo album generator (140) are linked and operated by dividing them into boxes, and the entire flow from the field smart terminal and public data API to the generation of the final integrated report can be checked.

[0060] The present invention described above has an integrated basic data DB module (110) that receives field inspection information including photos collected at the site, handwritten checklists, and basic measurement data, as well as equipment-specific history and environmental factor data for grade calculation correction, maps them to equipment-specific identification numbers (IDs), and stores them in an integrated database.

[0061] In addition, the present invention uses an attribute diagnosis-based environment-corrected comprehensive rating calculation engine (120) to calculate safety, durability, and usability scores of the equipment based on data extracted from a database, and to determine the final comprehensive performance rating by applying weights according to environmental stress factors.

[0062] The present invention also identifies the type of equipment and the type of measurement (e.g., at least one of electrical measurement, deterioration test, insulation resistance, wear measurement, strength test, corrosion inspection, crack measurement) by analyzing the visual features and metadata of the uploaded image using an AI multimodal photo / measurement type classifier (130).

[0063] In addition, the present invention generates a result report and a photo album by having a one-click report and photo album generator (140) collectively insert images automatically classified by overall performance rating results and measurement types into the corresponding fields of a report template.

[0064] Meanwhile, Figure 2 is a flowchart of the automatic database creation of railway equipment precision diagnosis data and the AI-based automatic photo album generation system applied to the present invention, showing the detailed processing procedure of the AI ​​multimodal photo and measurement type classifier and the one-click reporting module. It shows the process in which, after uploading field data, the AI ​​simultaneously analyzes the environment, object, type, and condition to perform comprehensive grade calculation and automatic photo classification in parallel, and finally automatically generates photo albums and comprehensive evaluation result sheets by measurement type, section, and date, which directly corresponds to a reduction of more than 90% in administrative work.

[0065] This can be explained in more detail as follows.

[0066] First, in the present invention, when the integrated basic data DB module (110) uploads field data & photos, the AI ​​multimodal transmits environmental analysis (e.g., temperature / humidity / weather / pollution / salt damage, etc.), object recognition (e.g., equipment type / identification / aging degree, etc.), type recognition (e.g., electricity / deterioration / corrosion / wear / cracks, etc.) and condition analysis (e.g., aging history / failure data, etc.) to an attribute diagnosis-based environment correction type comprehensive grade calculation engine (120).

[0067] Afterwards, the above attribute diagnosis-based environment correction type comprehensive grade calculation engine (120) calculates safety, durability, and usability as AE according to the comprehensive performance grade calculation.

[0068] Next, the AI ​​multimodal photo / measurement type classifier (130) performs automatic classification by measurement type (e.g., electrical / deterioration / insulation / wear / strength / corrosion / crack, etc.).

[0069] After the layout is configured, the one-click report and photo album generator (140) automatically generates a comprehensive evaluation result sheet and photo albums for each measurement type, section, and date.

[0071] The present invention, as described above, automatically constructs a database (DB) for full-cycle management by integrating heterogeneous data acquired in the field (e.g., photos, handwritten data, measurements, etc.) and external environmental factors (e.g., weather information) for correction into a standardized format; automatically calculates grades for safety, durability, and usability by combining and analyzing DB-based time-series data with environmental variables, and scientifically derives a final comprehensive performance grade by integrating these. Furthermore, it provides the effect of providing an intelligent engine that utilizes AI multimodal recognition technology to automatically classify randomly taken photos according to measurement types (e.g., electrical measurement, degradation test, insulation resistance, wear measurement, strength test, corrosion inspection, crack measurement, etc.) and generate an optimal photo layout. Industrial applicability

[0073] The technical concept of the present invention, an automatic database creation of precision diagnostic data for railway facilities and an AI-based automatic photo album generation system, is capable of repeating identical results in practice. In particular, since implementing such an invention can promote technological advancement and contribute to industrial development, it is fully worthy of protection.

[0074] No content Explanation of the symbols

[0075] <Explanation of symbols for major parts of the drawing> 100: Automatic DB Conversion of Railway Equipment Precision Diagnostic Data and AI-Based Automatic Photo Album Generation System 110: Integrated Basic Data DBization Module 120: Attribute Diagnosis-Based Environment-Corrected Comprehensive Rating Engine 130; AI Multimodal Photo / Measurement Type Classifier 140: One-click Report and Photo Album Generator

Claims

Claim 1 The invention relates to an automatic DB conversion of precision diagnostic data for railway equipment and an AI-based automatic photo album generation system (100), comprising: an integrated basic data DB conversion module (110) that receives photos, handwritten data, and basic measurement values ​​(Raw Data) of the railway equipment site from a field smart terminal, and maps and stores them in a relational database (RDBMS) by combining public data APIs and equipment aging history; an attribute diagnostic-based environmental correction type comprehensive grade calculation engine (120) that dynamically sets threshold values ​​and weights for each site through a variable diagnostic template engine, automatically determines an overall performance grade of A to E by reflecting environmental correction coefficients in safety, durability, and usability scores, and calculates environmental correction coefficients for each predefined environmental stress item in the algorithm result value by dynamically mapping a pre-set weight matrix based on the protocol for each railway equipment site; and automatically classifies and stores equipment objects, defect states, and environmental risk factors from collected images by combining them with measurement type tags, and extracts image feature vectors from field photo data to classify predefined equipment object types and deterioration states A railway equipment precision diagnostic data automatic DB conversion and AI-based photo album automatic generation system characterized by including: an AI multimodal photo and measurement type classifier (130) that automatically performs tagging according to measurement type mapping rules; and a one-click report and photo album generator (140) that automatically maps comprehensive grade data and automatically classified photos by measurement type to a legal report template to generate a document for distribution with one click. Claim 2 The railway equipment precision diagnosis data automatic DB conversion and AI-based photo album automatic generation system according to claim 1, wherein the integrated basic data DB conversion module (110) comprises: a field smart terminal (111) that transmits raw data of photos / handwritten notes / measurements to a collection server (113); a public data API (112) that automatically receives data on pollution, salt damage, and meteorological environmental factors of the relevant area shared by an external agency (e.g., Korea Meteorological Administration) through a public data API or web scraping; a collection server (113) that is connected to the field smart terminal (111) and the public data API (112), receives photos, handwritten notes, and measurement values ​​uploaded from the field, transmits them to a storage / processing pipeline, reduces data omissions and duplications, and collects them in a standard format; and an integrated precision diagnosis and environmental DB (114) that processes data from the collection server (113) and stores field inspection data, environmental data, and equipment history in one place based on equipment ID. Claim 3 A railway equipment precision diagnosis data automatic DB conversion and AI-based photo album automatic generation system according to claim 1, wherein the attribute diagnosis-based environment correction type comprehensive grade calculation engine (120) includes: a variable diagnosis and comprehensive evaluation engine (121) that dynamically sets items, thresholds, and weights by reflecting different protocols for each site / service, calculates inspection data based thereon, and automatically performs a comprehensive grade calculation logic; and a safety / durability / practicality comprehensive evaluation and environmental correction coefficient (122) that calculates safety, durability, and usability scores after performing the algorithm of the variable diagnosis and comprehensive evaluation engine (121), and then applies a correction coefficient according to environmental stress such as pollution and salt damage to objectively determine the final A~E comprehensive grade. Claim 4 The railway equipment precision diagnosis data automatic DB conversion and AI-based photo album automatic generation system according to claim 1, wherein the AI ​​multimodal photo / measurement type classifier (130) includes: an AI measurement type recognition / classification (131) that automatically determines what equipment / condition and what measurement type evidence the photo is by analyzing metadata regarding the photo and a preset photo type setting; and an automatic tagging & folderging (132) connected to the AI ​​measurement type recognition / classification (131), which attaches the measurement type, equipment, section, and date information determined by the AI ​​as tags and automatically organizes them into a folder / album structure according to the criteria. Claim 5 In claim 1, the one-click report and photo album generator (140) is characterized by dynamically configuring the layout of the photo album and automatically entering descriptions by combining one or more of the criteria for shooting date, track section / station, equipment type, and measurement type according to the user's selection, in a railway equipment precision diagnosis data automatic DB conversion and AI-based photo album automatic generation system.

Images