Passenger train valve maintenance informatization management method and system

Abstract

The invention discloses a passenger train valve maintenance informatization management method and system, and the method comprises the steps: collecting identity information, maintenance data and audio and video data in the maintenance process of a valve, automatically recognizing the identity information of the valve through a radio frequency recognition technology, and automatically collecting maintenance parameters through a detection unit, and generating original maintenance data; pre-processing the original maintenance data, and generating standardized pre-processed data through dual-architecture cooperative processing; performing transcoding processing on audio and video contents in the preprocessed data, converting multi-format original audio and video into a standardized format, and outputting standardized audio and video data; and establishing a valve whole life cycle tracing system, and associating and storing the identity information, the maintenance data and the audio and video data to form complete maintenance archive data. According to the invention, through automatic acquisition, dual-architecture collaboration, audio and video standardization and full-process tracing, intelligent management and quality improvement of valve maintenance data are realized, and the resource utilization efficiency is significantly optimized.

Description

Technical Field

[0001] This application relates to the field of information technology in railway equipment maintenance, specifically to information management methods and systems for the maintenance of valve components in railway passenger cars. Background Technology

[0002] As core components of the braking system, the maintenance quality of valves in railway passenger cars directly affects train operation safety. With the continuous growth of railway transport volume, traditional maintenance data management models are no longer sufficient to meet the current demands for efficient and accurate operations. Their limitations are mainly reflected in the following aspects.

[0003] In the data acquisition phase, traditional methods heavily rely on manual recording of valve model, manufacturing process, and test results. This is not only inefficient but also prone to errors and omissions, leading to incomplete or inaccurate information. More importantly, manual records are difficult to link with valve identification information in real time, posing significant challenges to subsequent data traceability and quality management. To address the identification issue, some solutions have introduced dedicated barcode scanning equipment. However, this introduces new problems such as high equipment dependence, increased procurement and maintenance costs, equipment susceptibility to damage, and operational inconvenience, impacting the stability and efficiency of data acquisition.

[0004] At the data management and system architecture level, existing systems mostly adopt a single client-server (CS) architecture or browser-server (BS) architecture, each with obvious shortcomings. While the CS architecture can handle complex local data well, its data sharing is poor, failing to meet the needs of remote collaborative access by multiple departments. On the other hand, while the BS architecture facilitates data sharing, it suffers from slow response speeds when dealing with massive amounts of historical maintenance records and test curve data, and struggles to support offline operations and local equipment control. Furthermore, the audio and video data generated during maintenance processes are often in inconsistent formats and large in size, resulting in low storage and transmission efficiency and poor cross-terminal compatibility, limiting its value in quality traceability and personnel training.

[0005] In summary, current railway passenger car valve maintenance data management faces challenges in all aspects of data collection, processing, storage, and application. There is an urgent need to build a comprehensive solution that integrates intelligent data collection, automatic uploading, dual-architecture collaborative processing, and audio and video data standardization to promote the transformation and upgrading of maintenance management towards intelligence and efficiency. Summary of the Invention

[0006] This application provides an information management method for the maintenance of valve components in railway passenger cars, which solves the problems of scattered maintenance data, difficulty in process traceability, and low management efficiency caused by the high reliance on manual data acquisition, single system architecture and function, and inefficient audio and video data management in the traditional maintenance mode.

[0007] This application is achieved through the following technical solution:

[0008] Firstly, this application provides an information management method for the maintenance of valve components in railway passenger cars, comprising the following steps:

[0009] Collect valve identification information, maintenance data, and audio / video data during valve maintenance. Automatically identify valve identification information using radio frequency identification technology and automatically collect maintenance parameters using a detection unit to generate raw maintenance data.

[0010] The raw maintenance data is preprocessed, and data processing and local operations are performed through a client-server architecture, while data sharing and remote access are achieved through a browser-server architecture, generating standardized preprocessed data.

[0011] Transcoding is performed on the audio and video content in the preprocessed data to convert the multi-format raw audio and video into a standardized format and output standardized audio and video data.

[0012] Establish a full lifecycle traceability system for valve components, linking and storing identity information, maintenance data, and audio / video data to form a complete maintenance record.

[0013] A further optimized solution involves collecting identification information, maintenance data, and audio / video data during valve maintenance. This is achieved by automatically identifying the valve's identity information using radio frequency identification (RFID) technology and automatically collecting maintenance parameters using a detection unit to generate raw maintenance data. Specifically, this includes the following steps:

[0014] By reading valve tag information using radio frequency identification technology, maintenance records are automatically created, generating identification data.

[0015] Based on the identity data, the detection unit collects mechanical and geometric parameters in real time, performs format verification on the collected parameter data, and realizes data association through device pairing authentication and identity binding process, and stores the verified parameter data in the local database.

[0016] The identity data and the verified parameter data are integrated to form the original maintenance data.

[0017] A further optimization is that the preprocessing step of the original maintenance data adopts a dual architecture of client-server and browser-server working together, specifically:

[0018] The client-server architecture performs local data processing and offline operations based on the validated parameter data, and outputs the local processing results.

[0019] The browser-server architecture receives the local processing result data and interacts with the client through a data synchronization protocol to achieve remote sharing and cross-terminal access;

[0020] The client and server exchange data through an internal network, and support offline caching and automatic data retransmission after network recovery.

[0021] A further optimization scheme is that the transcoding adopts an optimized algorithm based on an audio and video processing framework, including:

[0022] Perform decapsulation processing on audio and video content, and parse its container structure to separate the video stream and audio stream;

[0023] The separated video and audio streams are decoded separately to obtain the original data;

[0024] The original data is optimized through filter processing, including key area cropping and resolution adjustment, to obtain optimized video data;

[0025] Encode the optimized video data to obtain the encoded audio and video;

[0026] The encoding process is optimized and controlled, the encoded audio and video streams are encapsulated in a standardized format, and valve identity association encoding is embedded to obtain local processing result data.

[0027] A further optimization is that the transcoding process also includes:

[0028] An adaptive bitrate control algorithm is used to dynamically adjust quality parameters based on the complexity of the audio and video content;

[0029] An improved intra-frame prediction algorithm is introduced into video coding, and an edge adaptive mode is added;

[0030] Noise reduction algorithms are applied to audio data to filter out environmental noise.

[0031] A further optimized solution is that establishing a full lifecycle traceability system includes:

[0032] Assign a unique identifier to each valve;

[0033] Based on identity data, maintenance parameter data, and standardized audio and video data, construct identity-data-audio and video association rules;

[0034] It supports retrieving complete maintenance history records through valve identification information.

[0035] A further optimization is that the method also includes maintenance process management:

[0036] The maintenance process is divided into multiple standardized workstations;

[0037] Maintenance data is entered in real time at each standardized workstation via terminal equipment.

[0038] Enables collaborative information flow between standardized workstations to support parallel maintenance of multiple types of valves.

[0039] Secondly, this application provides an information management system for the maintenance of valve components in railway passenger cars, used to implement the information management method for the maintenance of valve components in railway passenger cars as described above, including:

[0040] The data acquisition module is used to collect the identification information, maintenance data and audio and video data during the valve maintenance process. It automatically identifies the valve identification information through radio frequency identification technology and automatically collects maintenance parameters using the detection unit to generate raw maintenance data.

[0041] The data processing module is communicatively connected to the data acquisition module and is used to preprocess the raw maintenance data. It performs data processing and local operations through a client-server architecture, and simultaneously realizes data sharing and remote access through a browser-server architecture, generating standardized preprocessed data.

[0042] The audio and video processing module is communicatively connected to the data processing module and is used to perform transcoding processing on the audio and video content in the preprocessed data, convert the multi-format raw audio and video into a standardized format, and output standardized audio and video data.

[0043] The data storage module is communicatively connected to the audio and video processing module and is used to establish a full life cycle traceability system for valve components, and to associate and store identity information, maintenance data and audio and video data to form complete maintenance record data.

[0044] Further optimizations include:

[0045] The maintenance operation management subsystem is used to achieve standardized management of maintenance processes.

[0046] The data analysis subsystem is used for multi-dimensional statistical analysis and quality early warning of maintenance data;

[0047] The interface service module is used for data interaction with the enterprise's internal MRO system and environmental monitoring system.

[0048] Thirdly, this application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores an information management program for the maintenance of railway passenger car valves, wherein when the information management program for the maintenance of railway passenger car valves is executed by a processor, it implements the steps of the information management method for the maintenance of railway passenger car valves as described above.

[0049] Compared with the prior art, this application has the following advantages and beneficial effects:

[0050] By using radio frequency identification technology and detection units, the valve identification information and maintenance parameters can be automatically collected, which effectively improves the accuracy and efficiency of data acquisition.

[0051] By leveraging the collaborative processing of a client-server and browser-server dual architecture, the system can perform complex local calculations and offline operations while ensuring remote data sharing and cross-terminal access capabilities, thereby enhancing the system's applicability and scalability.

[0052] For multi-format audio and video content generated during maintenance, standardized transcoding is used to achieve efficient compression and unified format output, significantly reducing storage and transmission burden;

[0053] Ultimately, by establishing a full lifecycle traceability system, identity information, maintenance data, and audio-visual content are integrated and stored together to form a complete and traceable maintenance file, thereby improving maintenance quality, strengthening the traceability capability throughout the entire process, and ultimately optimizing resource utilization. Attached Figure Description

[0054] To more clearly illustrate the technical solutions of the exemplary embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0055] Figure 1 A flowchart of an information management method for the maintenance of railway passenger car valves provided in this application embodiment;

[0056] Figure 2 A three-layer architecture diagram of the digital valve maintenance system provided in this application embodiment;

[0057] Figure 3 This is a schematic diagram of the standardized transcoding process for maintenance audio and video provided in an embodiment of this application;

[0058] Figure 4 The overall architecture of the valve maintenance information platform provided in the embodiments of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the embodiments and accompanying drawings. The illustrative embodiments and descriptions of this application are only for explaining this application and are not intended to limit this application.

[0060] First, some of the technical terms used in this application will be explained to help those skilled in the art understand this application.

[0061] CS: Client-Server architecture;

[0062] BS: Browser-Server architecture;

[0063] RFID: Radio Frequency Identification;

[0064] MRO: Maintenance, Repair and Operations;

[0065] FFmpeg: Fast Forward MPEG, an open-source multimedia processing framework;

[0066] AAC: Advanced Audio Coding;

[0067] HEVC: High Efficiency Video Coding;

[0068] CRF: Constant Rate Factor;

[0069] YUV: A color coding system (consisting of luminance Y and two chromaticity components U and V);

[0070] PCM: Pulse Code Modulation;

[0071] LC: Low Complexity;

[0072] ETL: Extract-Transform-Load.

[0073] like Figure 1 As shown, the information-based method for the maintenance of railway passenger car valves provided in this application specifically includes the following steps:

[0074] Step S1: Collect the identification information, maintenance data and audio / video data during the valve maintenance process. Automatically identify the valve identification information through radio frequency identification technology, and automatically collect maintenance parameters using the detection unit to generate raw maintenance data.

[0075] Step S2: Preprocess the raw maintenance data by performing data processing and local operations through a client-server architecture, while simultaneously enabling data sharing and remote access through a browser-server architecture, thereby generating standardized preprocessed data;

[0076] Step S3: Perform transcoding processing on the audio and video content in the preprocessed data, convert the multi-format original audio and video into a standardized format, and output standardized audio and video data;

[0077] Step S4: Establish a full lifecycle traceability system for valve components, link and store identity information, maintenance data and audio / video data to form complete maintenance record data.

[0078] This embodiment ensures the accuracy and integrity of the data source through automatic data collection and identity binding; it balances the efficiency of local processing with the convenience of data sharing through dual-architecture collaborative processing; it significantly reduces storage and transmission costs and improves data availability by utilizing standardized audio and video transcoding; and finally, by establishing a full lifecycle traceability system, it integrates scattered data into electronic archives with higher value density, thereby greatly improving the overall quality control capabilities, process traceability efficiency, and decision support level of maintenance operations.

[0079] In this application, the valve refers to a brake valve.

[0080] The effective implementation of the above method relies on an integrated system architecture. Specifically, this application constructs a three-tiered digital management system encompassing a data layer, a service layer, and an application layer by integrating a hybrid client-server (CS) and browser-server (BS) architecture. The three-tiered architecture is as follows: Figure 2 As shown:

[0081] The application layer provides data display and interactive interfaces for different roles through various terminals such as workstation terminal operation screens, user computers, and large floor-standing screens. The service layer is the core business layer, adopting a hybrid CS / BS architecture: the CS architecture's "Valve Maintenance Operation System" directly serves the entire process of workstation operations and equipment control, including revenue, disassembly, cleaning, grinding, maintenance, testing, and expenditure; the BS architecture's "Brake Valve Maintenance Information System" focuses on backend management functions such as workstation and testing information management, data statistics, and system management, and achieves data interoperability with the CS system and other external systems through interface services. The data processing and analysis layer has a dedicated "Brake Valve Maintenance Data Analysis System" that performs in-depth statistical and visual analysis of maintenance, testing, and fault data from the lower layer. The bottom layer is the data layer, consisting of application servers and file servers, used to store structured business data (such as maintenance data and testing data) and unstructured file data (such as audio, video, images, and backup files), providing unified data support for upper-layer applications. Data exchange and business collaboration between different levels are achieved through standard interfaces, jointly realizing a closed-loop digital process from on-site operations to management decisions.

[0082] Overall platform architecture as follows Figure 4 As shown:

[0083] This platform uses an internal LAN as its data hub, constructing a hierarchical and collaborative information management system. The entire system follows a full-chain logic of "data acquisition and storage, processing and transcoding, analysis and application," manifested in a clear three-layer architecture. At the bottom layer, the "Valve Maintenance Operation System," designed for on-site operations, constitutes the data layer. It integrates modules such as image acquisition, data acquisition, fault acquisition, and workstation management. Based on a client-server (CS) architecture, it achieves source data acquisition and process control during maintenance, and centrally stores all raw data, test data, and audio / video files on a file server and database. The middle layer is the service layer, based on a browser-server (BS) architecture, carrying core data processing and service functions. The "Valve Maintenance Information System," as the main business platform, is responsible for web services such as test information management, workstation enterprise management, report aggregation, and data statistics. It also collaborates with the independent "Valve Maintenance Data Analysis System" to conduct in-depth analysis of lower-layer data, performing fault diagnosis, leakage analysis, and pass rate statistics. At the top application layer, the processing results are comprehensively and visually displayed through diverse terminal interfaces. Information such as workstation data monitoring and maintenance data statistics charts serves workstation terminals, computers, and management screens, meeting different needs from on-site operation to management decision-making.

[0084] The system's data flow begins at the maintenance work frontline. Various data acquired through RFID, intelligent tooling and sensors, and audio / video acquisition equipment are first stored in a local database and file server. Subsequently, the data is transmitted via the internal network and integrated into both the valve maintenance information system (BS architecture), which focuses on process information management, and the valve maintenance data analysis system (BS architecture), which focuses on in-depth analysis and decision support, to meet different business needs. To further break down information silos, this system also interconnects with existing enterprise systems (such as the MRO system and environmental monitoring system) through data interfaces, expanding the boundaries of data application.

[0085] All collected, processed, and correlated data is ultimately displayed in multiple dimensions through various devices such as large visualization screens, computer terminals, and workstation operation screens. This not only presents key information such as production line overviews and quality analysis charts in real time, meeting the in-depth analysis needs of managers, but also provides core data support for quality retrospective, fault diagnosis, and process optimization based on the complete and traceable valve maintenance records formed.

[0086] In one embodiment, step S1: collecting identification information, maintenance data, and audio / video data during valve maintenance, automatically identifying valve identification information using radio frequency identification technology, and automatically collecting maintenance parameters using a detection unit to generate raw maintenance data, specifically includes the following steps:

[0087] Step S11: The identification code information in the valve tag is read using RFID technology to automatically create a corresponding electronic maintenance file and generate uniquely identified authentication data. Specifically, this process uses a data association method between RFID tags and intelligent testing equipment. The valve tag information is read by an RFID reader to automatically create a uniquely identified electronic maintenance file and generate authentication data. Equipment pairing authentication can be achieved via Bluetooth 5.0 or a USB handshake protocol. The identity binding process includes associating the RFID tag ID with the testing unit serial number.

[0088] Step S12: Based on the generated identity authentication data, control the corresponding detection unit to collect the mechanical performance parameters and geometric dimension parameters of the valve in real time, and perform format standardization and rationality verification on the collected parameter data. Data that passes the verification is stored in a local database to form a standardized verification parameter set. Specifically, the detection unit includes intelligent detection devices such as intelligent torque wrenches and vernier calipers, which communicate with the client system via Bluetooth 5.0 or USB interface to upload parameters such as torque and dimensions in real time. The collected parameter data needs to undergo format standardization and rationality verification. After passing the verification, it is stored in the local database to form a standardized verification parameter set. The automatic data verification process can use the CRC check algorithm to ensure the correctness of the parameter data format.

[0089] Step S13: Integrate the identity authentication data with the standardized verification parameter set to form complete original maintenance data containing identity information and maintenance parameters. This integration process relies on the collaborative implementation of functional modules such as image acquisition, RFID reader configuration, intelligent equipment tool configuration, and workstation management to ensure a one-to-one correspondence between identity information and maintenance parameters, ultimately forming a complete data record that can be used for subsequent analysis.

[0090] This embodiment employs a multi-technology integrated acquisition mechanism, integrating RFID contactless identification technology with various intelligent testing equipment to achieve automatic association and real-time uploading of valve identification information and maintenance parameters. Specifically, based on the existing production organization mode of the valve maintenance production line, the process layout can be rationally optimized, dividing key workstations such as revenue decomposition, ultrasonic cleaning, grinding, spring testing, maintenance, and testing. Furthermore, a unified acquisition platform can be designed to network key process equipment such as spring testing machines, valve testing benches, grinding equipment, and ultrasonic cleaning machines, integrating intelligent sensors and data acquisition terminals to achieve millisecond-level automatic acquisition of spring performance parameters, test data, and process environment data, thereby expanding the coverage and real-time performance of data acquisition.

[0091] In one embodiment, step S2: preprocessing the raw maintenance data, performing data processing and local operations through a client-server architecture, and simultaneously achieving data sharing and remote access through a browser-server architecture, to generate standardized preprocessed data, specifically including the following steps:

[0092] Step S21: Based on the generated raw maintenance data, perform local complex data processing, offline operations, and audio / video preprocessing through a client-server architecture, and output the pre-processed local result data. Specifically, this process is achieved by developing and deploying a dedicated valve maintenance operation system (CS architecture). This system solidifies the standard maintenance process and procedure requirements, and realizes real-time data entry, automatic acquisition of process parameters, and information collaborative flow between workstations through terminals deployed at each standardized workstation.

[0093] Step S22: The output local result data is converted and optimized for transmission through a browser-server architecture to enable remote multi-terminal access and data sharing, generating standardized preprocessed data; preferably, this function is achieved by building a valve maintenance information system (BS architecture). This system typically deploys core modules including a homepage dashboard, workstation maintenance information, test information, report statistics, data management, and system management, focusing on information-based control and remote data sharing of the maintenance process;

[0094] Step S23: Establish a real-time data exchange channel between the client-server architecture and the browser-server architecture through a data synchronization mechanism to ensure data consistency under the two architectures and provide automatic data recovery capability in case of network anomalies; specifically, the data synchronization mechanism follows the collaborative working mechanism of CS+BS dual architecture, including a dedicated data synchronization protocol, a local offline caching strategy, and automatic data retransmission logic after network recovery, thereby ensuring the continuity and reliability of the data processing flow; preferably, step S2 adopts a collaborative design of CS and BS dual architecture, and achieves data consistency through a data synchronization protocol (such as based on HTTP long polling or WebSocket) and an offline caching strategy.

[0095] In one embodiment, such as Figure 3 As shown, step S3 involves performing transcoding on the audio and video content in the preprocessed data, converting the multi-format original audio and video into a standardized format, and outputting standardized audio and video data.

[0096] Step S31: Perform format analysis and decapsulation on the audio and video content in the output standardized preprocessed data to separate independent video and audio streams, laying the foundation for subsequent splitting processing. This process achieves multi-format audio and video decapsulation by calling the libavformat multimedia format processing library of the FFmpeg framework to parse the container structure of the original audio and video in heterogeneous formats such as MOV and AVI collected at the maintenance site, and separate the video and audio streams into independent metadata streams.

[0097] Step S32: Decode the separated video and audio streams separately, converting the compressed data into the original data format to eliminate compatibility issues caused by different encoding formats, and obtain the decoded original audio and video data. Preferably, this audio and video stream decoding and conversion is completed using FFmpeg's libavcodec codec library, performing decoding operations on the separated video and audio streams respectively, converting the compressed video data into original video frames in YUV format, and simultaneously converting the audio data into original audio data in PCM format.

[0098] Step S33: Optimize the quality of the decoded raw audio and video data using a filter processing algorithm, including key area enhancement, noise filtering, and adaptive resolution adjustment, to improve the usability of the audio and video content and obtain optimized audio and video data. Specifically, this raw data filter optimization process is implemented based on FFmpeg's libavfilter filter library: at the video level, key maintenance areas are intelligently cropped to retain the core operation screen, and the resolution is dynamically adjusted to adapt to the needs of storage resources and network transmission bandwidth; at the audio level, noise reduction algorithms are used to filter environmental interference noise at the maintenance site, improving the clarity of voice commands and equipment operation sounds.

[0099] Step S34: Re-encode the optimized audio and video data using an efficient encoding algorithm to reduce data size while maintaining quality, outputting encoded data in a standard format. This step applies a customized encoding processing strategy, performing targeted encoding on the optimized original data. The video encoding uses a high-efficiency H.264 or HEVC encoder, and integrates innovative algorithms to optimize performance. Specifically, the implementation is as follows:

[0100] Step S341: Adaptive CRF Bitrate Control Algorithm: The CRF (Constant Quality Factor) value is dynamically adjusted based on the complexity of the audio and video content. By analyzing the motion vector density and texture complexity of video frames, the content is divided into simple scenes (e.g., static device display), medium scenes (e.g., routine operation processes), and complex scenes (e.g., dynamic fault demonstrations). Specifically, simple scenes are set to CRF=28 to balance compression ratio and quality, medium scenes are set to CRF=23 to ensure clear image quality, and complex scenes are set to CRF=18 to avoid detail loss; and this is achieved through the formula... The CRF value is dynamically calculated; where S is the scene simplicity factor, calculated based on inter-frame difference and texture complexity. The higher the value, the simpler the scene, and the value range is 0-1; M is the scene complexity factor, calculated based on motion vector amplitude and detail richness. The higher the value, the more complex the scene, and the value range is 0-1, achieving an intelligent balance between quality and volume.

[0101] Step S342: Improve the intra-frame prediction algorithm: Targeting the characteristics of well-defined equipment textures and distinct edge features in inspection videos, optimize the intra-frame prediction mode selection. Based on the original nine intra-frame prediction modes in H.264, a new "device edge adaptive mode" is added. This involves optimizing the mode selection strategy based on the intra-frame prediction modes provided by the H.264 standard: Extracting video frame edge information using the Sobel operator to determine the edge direction, and prioritizing the standard prediction mode parallel to the edge direction; Extracting video frame edge information using the Sobel operator, determining the edge direction, and prioritizing the prediction mode parallel to the edge to reduce prediction residuals; Simultaneously, a mode decision threshold δ (range 5-15) is introduced, dynamically adjusted based on the device's CPU load and memory usage to balance coding efficiency and computational resource consumption. When the rate-distortion cost difference between candidate modes is less than δ, the mode with lower computational complexity is directly selected to reduce coding time.

[0102] Audio encoding employs the LC (low complexity) configuration of the AAC encoder, balancing encoding speed and audio quality. These algorithms work together to ensure that the encoding process improves efficiency while optimizing output quality.

[0103] Step S35: Standardize and encapsulate the encoded audio and video streams, embedding metadata associated with the valve's identity to ultimately generate standardized audio and video data in a unified format. Specifically, in this step, the encoded audio and video streams are re-encapsulated into the universal MP4 format using the libavformat library. During the encapsulation process, metadata associated with the unique valve identification code (consistent with the RFID tag identifier) ​​recorded in the audio and video segment is embedded simultaneously, achieving precise binding between the audio and video files and the valve maintenance records.

[0104] This embodiment implements a customized audio and video transcoding solution based on the FFmpeg framework. Through a complete process of "de-encapsulation-decoding-filtering-encoding optimization-encapsulation," it standardizes original multi-format audio and video into MP4 format. This process is adapted to the scenario characteristics of audio and video recordings used in railway passenger car valve maintenance. Based on the basic encoding logic of FFmpeg, it innovatively designs a combined algorithm of "adaptive CRF bitrate control + improved intra-frame prediction + intelligent audio optimization," aiming to simultaneously improve transcoding efficiency, compression ratio, and content quality.

[0105] In one embodiment, step S4: establishing a valve component lifecycle traceability system, associating and storing identity information, maintenance data, and audio / video data to form complete maintenance record data, specifically includes the following steps:

[0106] Step S41: Assign a unique identifier to each valve and establish an identification management system based on the generated identity authentication data to ensure that the identity information of each valve is unique and traceable; preferably, the unique identifier can be realized through physical carriers such as laser-etched QR codes or RFID electronic tags, providing the valve with a tamper-proof "digital ID card" and supporting continuous addition and updating of data throughout its entire life cycle;

[0107] Step S42: Integrate and link identity authentication data, standardized verification parameter sets, and standardized audio and video data to construct an integrated data association rule for "identity-parameter-audio and video". Specifically, this integrated data association rule follows the core logic of "three bindings": deeply binding valve identification with raw material information, production process information (such as processing parameters and quality inspection results), and after-sales maintenance information, thereby breaking down information silos and forming a complete "production-maintenance-application" data chain. In this process, maintenance data, test data, fault data, and workstation data from various standardized workstations (such as grinding, assembly, and testing) are all integrated, providing core data support for the traceability system.

[0108] Step S43: Based on the established data association rules, develop a data retrieval and service interface to support querying complete maintenance history records through valve identification information and output traceable maintenance archive data. Preferably, the developed data retrieval and service interface can be integrated into a BS architecture information system to form a comprehensive platform including a homepage dashboard, workstation maintenance information, test information, report statistics, and other functions. Users can scan the valve identification mark with a tablet or handheld device to access real-time information on the entire process from warehousing disassembly, cleaning, grinding, assembly to testing, along with associated audio and video materials, greatly improving traceability efficiency.

[0109] This embodiment constructs a full lifecycle traceability system, deeply integrating valve identification with full-process maintenance data and audio / video files through unique identifiers to form a complete closed-loop data chain. This system not only enables precise traceability from raw materials to scrap, quickly locating quality issues and assigning responsibility, but also provides intelligent statistical analysis of diverse data such as production, quality, personnel, and equipment through a data analysis system. This provides data-driven decision support for optimizing maintenance processes, predictive maintenance, and lean management, ultimately transforming quality control from "passive response" to "proactive prevention."

[0110] In one embodiment, after establishing a valve component lifecycle traceability system, associating and storing identity information, maintenance data, and audio / video data to form complete maintenance record data, step S4 further includes the following steps:

[0111] Step S5: The generated traceable maintenance archive data is displayed in multiple dimensions to provide data support for quality analysis, fault diagnosis, and process optimization, forming a complete closed loop for maintenance quality management. Specifically, by configuring a visual dashboard, multiple sub-topics such as production line overview, function introduction, quality analysis, and workstation management are integrated to meet the drill-down data analysis needs of multi-level managers from macro to micro. Furthermore, the application layer can deploy three types of terminal devices: workstation terminal operation screens, user computers, and floor-standing large screens, to display core information such as maintenance progress, key data statistics, and quality trends in real time and intuitively, realizing comprehensive visual monitoring and management of the maintenance process and results.

[0112] In one embodiment, the method further includes maintenance process management:

[0113] The maintenance process is divided into multiple standardized workstations; specifically, the standardized workstations include 11 key workstations such as income decomposition workstation, ultrasonic cleaning workstation, grinding workstation, spring testing workstation, delivery workstation, maintenance workstation, valve assembly workstation, testing workstation, intermediate testing workstation, and expenditure workstation, so as to realize standardized assembly line operation and quality control.

[0114] Maintenance data is entered in real time at each standardized workstation via terminal equipment.

[0115] Enables collaborative information flow between standardized workstations to support parallel maintenance of multiple types of valves.

[0116] In one embodiment, the method further includes the management of the maintenance process flow, specifically implemented in the following ways:

[0117] The entire valve repair process is divided into multiple standardized workstations, forming a standardized assembly line operation and quality control chain. Specifically, based on the production organization model of the valve repair production line, the entire repair process is divided into multiple standardized workstations, forming a standardized assembly line operation and quality control chain. These standardized workstations include key operational nodes such as revenue breakdown, ultrasonic cleaning, grinding, spring testing, repair, and testing, and can be further extended to stages such as distribution, valve assembly, intermediate component testing, and expenditure, to achieve comprehensive process coverage.

[0118] Terminal devices are deployed at each standardized workstation, allowing operators to input or automatically collect maintenance data for that workstation in real time. Specifically, by integrating RFID contactless identification technology with various intelligent testing equipment (such as intelligent torque wrenches and vernier calipers), and designing a unified data acquisition platform, key process equipment such as spring testing machines, valve testing benches, grinding equipment, and ultrasonic cleaning machines are networked, integrating intelligent sensors and data acquisition terminals. This enables millisecond-level automatic acquisition and real-time uploading of valve identification information and maintenance parameters such as spring performance parameters, test data, and process environment data, providing a highly real-time and comprehensive data foundation for end-to-end management.

[0119] By using an information system, information collaboration and automatic flow between standardized workstations can be achieved, thereby supporting parallel maintenance and full-process traceability of multiple types and batches of valves. Specifically, based on the above workstation division and data collection, terminal equipment is deployed at each standardized workstation for operators to input or for the system to automatically collect maintenance data for that workstation in real time. Through the upper-level information system, the automatic collaborative flow of information between workstations is driven, thereby supporting parallel maintenance, full-process traceability, and decision support for multiple types and batches of valves.

[0120] Secondly, this application provides an information management system for the maintenance of valve components in railway passenger cars, used to implement the information management method for the maintenance of valve components in railway passenger cars as described above, including:

[0121] The data acquisition module is used to collect the identification information, maintenance data and audio and video data during the valve maintenance process. It automatically identifies the valve identification information through radio frequency identification technology and automatically collects maintenance parameters using the detection unit to generate raw maintenance data.

[0122] The data processing module is communicatively connected to the data acquisition module and is used to preprocess the raw maintenance data. It performs data processing and local operations through a client-server architecture, and simultaneously realizes data sharing and remote access through a browser-server architecture, generating standardized preprocessed data.

[0123] The audio and video processing module is communicatively connected to the data processing module and is used to perform transcoding processing on the audio and video content in the preprocessed data, convert the multi-format raw audio and video into a standardized format, and output standardized audio and video data.

[0124] The data storage module is communicatively connected to the audio and video processing module and is used to establish a full life cycle traceability system for valve components, and to associate and store identity information, maintenance data and audio and video data to form complete maintenance record data.

[0125] Meanwhile, this architecture, through a full-link design of "application layer (data display) - service layer (data acquisition + processing and analysis) - data layer (data storage)," combined with the functional division of a CS / BS dual architecture, achieves full-process digital management of valve maintenance. For example... Figure 4 As shown, the valve maintenance information platform is built around the concept of "maintenance data collection, storage, analysis, and application." Its core modules include the valve maintenance operation system (responsible for front-line business execution), the intermediate support layer (connecting the database and file server via an internal LAN to achieve data exchange), and the valve maintenance information system and data analysis system on the right (focusing on business management and statistical analysis, respectively). The data flow forms a closed loop of "business execution - data accumulation - management analysis," providing contextual support for transcoding.

[0126] In one embodiment, the railway passenger car valve maintenance information management system of this application further includes:

[0127] The maintenance operation management subsystem is used to achieve standardized management of maintenance processes. This system achieves standardized operation of maintenance processes by dividing and managing multiple standardized workstations such as income breakdown workstation, ultrasonic cleaning workstation, grinding workstation, spring testing workstation, delivery workstation, maintenance workstation, valve assembly workstation, testing workstation, intermediate testing workstation, and expenditure workstation.

[0128] The data analysis subsystem is used for multi-dimensional statistical analysis and quality early warning of maintenance data;

[0129] The interface service module is used for data interaction with the enterprise's internal MRO system and environmental monitoring system.

[0130] The functions of each module in the above-mentioned railway passenger car valve maintenance information management system correspond to the steps in the above-mentioned railway passenger car valve maintenance information management method embodiment, and their functions and implementation processes will not be described in detail here.

[0131] Thirdly, embodiments of this application provide an information management device for the maintenance of valve components in railway passenger cars. This information management device for the maintenance of valve components in railway passenger cars can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0132] In this embodiment, the railway passenger car valve maintenance information management equipment may include a processor, a memory, a communication interface, and a communication bus.

[0133] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0134] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting internal components of the railway passenger car valve maintenance information management equipment, as well as interfaces used for interconnecting the equipment with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0135] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0136] The processor can be a general-purpose processor, which can call the railway passenger car valve maintenance information management program stored in the memory and execute the railway passenger car valve maintenance information management method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the railway passenger car valve maintenance information management program is called can be referred to the various embodiments of the railway passenger car valve maintenance information management method of this application, and will not be repeated here.

[0137] Fourthly, embodiments of this application also provide a readable storage medium.

[0138] The present application has a readable storage medium storing a railway passenger car valve maintenance information management program, wherein when the railway passenger car valve maintenance information management program is executed by a processor, it implements the steps of the railway passenger car valve maintenance information management method described above.

[0139] The method implemented when the railway passenger car valve maintenance information management program is executed can be referred to in the various embodiments of the railway passenger car valve maintenance information management method of this application, and will not be repeated here.

[0140] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An information management method for the maintenance of valve components in railway passenger cars, characterized in that, Includes the following steps: Collect valve identification information, maintenance data, and audio / video data during valve maintenance. Automatically identify valve identification information using radio frequency identification technology and automatically collect maintenance parameters using a detection unit to generate raw maintenance data. The raw maintenance data is preprocessed, and data processing and local operations are performed through a client-server architecture. At the same time, data sharing and remote access are achieved through a browser-server architecture, generating standardized preprocessed data. Transcoding is performed on the audio and video content in the preprocessed data to convert the multi-format raw audio and video into a standardized format and output standardized audio and video data. Establish a full lifecycle traceability system for valve components, linking and storing identity information, maintenance data, and audio / video data to form a complete maintenance record.

2. The information management method for the maintenance of railway passenger car valves as described in claim 1, characterized in that, The process of collecting identification information, maintenance data, and audio / video data during valve maintenance involves automatically identifying valve identification information using radio frequency identification (RFID) technology and automatically collecting maintenance parameters using a detection unit to generate raw maintenance data. Specifically, this includes the following steps: By reading valve tag information using radio frequency identification technology, maintenance records are automatically created, generating identification data. Based on the identity data, the detection unit collects mechanical and geometric parameters in real time, performs format verification on the collected parameter data, and realizes data association through device pairing authentication and identity binding process, storing the verified parameter data in the local database. The identity data and the verified parameter data are integrated to form the original maintenance data.

3. The information management method for the maintenance of railway passenger car valves as described in claim 2, characterized in that, The preprocessing step of the original maintenance data adopts a dual architecture of client-server and browser-server working together, specifically as follows: The client-server architecture performs local data processing and offline operations based on the validated parameter data, and outputs the local processing results. The browser-server architecture receives the local processing result data and interacts with the client through a data synchronization protocol to achieve remote sharing and cross-terminal access; The client and server exchange data through an internal network, and support offline caching and automatic data retransmission after network recovery.

4. The information management method for the maintenance of railway passenger car valves as described in claim 3, characterized in that, The transcoding employs an optimized algorithm based on an audio / video processing framework, including: Perform decapsulation processing on audio and video content, and parse its container structure to separate the video stream and audio stream; The separated video and audio streams are decoded separately to obtain the original data; The original data is optimized through filter processing, including key area cropping and resolution adjustment, to obtain optimized video data; Encode the optimized video data to obtain the encoded audio and video; The encoding process is optimized and controlled, the encoded audio and video streams are encapsulated in a standardized format, and valve identity association encoding is embedded to obtain local processing result data.

5. The information management method for the maintenance of railway passenger car valves as described in claim 4, characterized in that, The transcoding process also includes: An adaptive bitrate control algorithm is used to dynamically adjust quality parameters based on the complexity of the audio and video content; An improved intra-frame prediction algorithm is introduced into video coding, and an edge adaptive mode is added; Noise reduction algorithms are applied to audio data to filter out environmental noise.

6. The information management method for the maintenance of railway passenger car valves as described in claim 1, characterized in that, The establishment of a full lifecycle traceability system includes: Assign a unique identifier to each valve; Based on identity data, maintenance parameter data, and standardized audio and video data, construct identity-data-audio and video association rules; It supports retrieving complete maintenance history records through valve identification information.

7. The information management method for the maintenance of railway passenger car valves as described in claim 1, characterized in that, The method also includes maintenance process management: The maintenance process is divided into multiple standardized workstations; Maintenance data is entered in real time at each standardized workstation via terminal equipment. Enables collaborative information flow between standardized workstations to support parallel maintenance of multiple types of valves.

8. A railway passenger car valve maintenance information management system, used to implement the railway passenger car valve maintenance information management method as described in any one of claims 1-7, characterized in that, include: The data acquisition module is used to collect the identification information, maintenance data and audio and video data during the valve maintenance process. It automatically identifies the valve identification information through radio frequency identification technology and automatically collects maintenance parameters using the detection unit to generate raw maintenance data. The data processing module is communicatively connected to the data acquisition module and is used to preprocess the raw maintenance data. It performs data processing and local operations through a client-server architecture, and at the same time realizes data sharing and remote access through a browser-server architecture, generating standardized preprocessed data. The audio and video processing module is communicatively connected to the data processing module and is used to perform transcoding processing on the audio and video content in the preprocessed data, convert the multi-format raw audio and video into a standardized format, and output standardized audio and video data. The data storage module is communicatively connected to the audio and video processing module and is used to establish a full life cycle traceability system for valve components, and to associate and store identity information, maintenance data and audio and video data to form complete maintenance record data.

9. The railway passenger car valve maintenance information management system as described in claim 8, characterized in that, Also includes: The maintenance operation management subsystem is used to achieve standardized management of maintenance processes. The data analysis subsystem is used for multi-dimensional statistical analysis and quality early warning of maintenance data; The interface service module is used for data interaction with the enterprise's internal MRO system and environmental monitoring system.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a railway passenger car valve maintenance information management program, wherein when the railway passenger car valve maintenance information management program is executed by a processor, it implements the steps of the railway passenger car valve maintenance information management method as described in any one of claims 1 to 7.

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