Wheelset condition monitoring and management system

Abstract

The application discloses a wheel set state monitoring and management system which comprises an off-vehicle data monitoring unit, a train data management host and a remote data center system. The off-vehicle data monitoring unit comprises a plurality of axle end data acquisition nodes installed on axle ends, the axle end data acquisition nodes comprise a signal acquisition system and an edge computing system, and are used for acquiring, calculating and sending state data of a single wheel set. The train data management host comprises an on-vehicle computing power system and a power module arranged on a train, and the on-vehicle computing power system is used for identifying and managing the state of wheel sets and bearings. The remote data center system communicates with the train data management host, and is used for receiving, storing, monitoring and managing the wheel set data of the train. The application significantly improves system integration and information completeness, effectively improves the synchronization of multi-sensing data, enhances the reliability and stability of long-term monitoring, and endows the wheel set with intelligent self-perception and self-identification capabilities.

Description

Technical Field

[0001] This invention relates to the field of rail vehicle technology, and in particular to a wheelset condition monitoring and management system. Background Technology

[0002] In the field of wheelset condition monitoring and management technology, existing technologies mainly revolve around core areas such as sensor monitoring, data processing, fault diagnosis, and full lifecycle management.

[0003] Early technical solutions focused on offline or simple online detection of single parameters, such as using vibration sensors or strain gauges to periodically collect mechanical load data on wheelsets and using threshold comparisons to provide early warnings of anomalies. With the development of the Internet of Things and embedded systems, subsequent solutions integrated multi-source sensing technologies. These used arrays of acceleration, temperature, and acoustic sensors deployed at the axle box or wheel spokes to achieve parallel data acquisition and wireless transmission of conditions such as wheelset tread damage, bearing temperature rise, and out-of-roundness. However, these solutions still have room for improvement in terms of data correlation and real-time performance.

[0004] In recent years, wheelset monitoring has evolved towards greater intelligence and systematization. On the one hand, edge computing architecture has been introduced, embedding lightweight algorithm models into onboard terminals to achieve real-time diagnosis and early warning of local features such as initial crack initiation and polygonal wear. On the other hand, by combining digital twins and big data platforms, a health management system covering the entire process of wheelset design, operation, and maintenance has been constructed. Through the fusion analysis of historical data and operating conditions, remaining life prediction and condition-based maintenance decision optimization can be achieved. However, existing technologies still face challenges in terms of high integration of multiple sensors, high-precision monitoring, and long-term monitoring reliability, requiring further technological integration and innovative breakthroughs.

[0005] The statements herein provide only background information in relation to this invention and do not necessarily constitute prior art. Summary of the Invention

[0006] The purpose of this invention is to provide a wheelset condition monitoring and management system to solve problems such as low integration, poor synchronization of multi-sensor data, incomplete fusion diagnostic information, and poor long-term monitoring reliability.

[0007] To achieve the above objectives, the present invention provides a wheelset condition monitoring and management system, comprising: an undercarriage data monitoring unit, a train data management host, and a remote data center system; The under-vehicle data monitoring unit includes multiple axle-end data acquisition nodes, which are installed on the axle ends and used to collect, calculate, and transmit status data of individual wheelsets. Each axle-end data acquisition node includes a signal acquisition system and an edge computing system. The signal acquisition system is used to realize the spatiotemporal synchronous acquisition of acceleration, temperature, impact, and speed signals and power management. The edge computing system is used to realize audio and video acquisition and the spatiotemporal synchronization of audio and video, acceleration, temperature, impact, and speed signals. The train data management host is deployed on the train and communicates with the axle-end data acquisition nodes. It is used to collect status data of all wheelsets of the entire train sent by all the axle-end data acquisition nodes, and to identify and manage the status of wheelsets and bearings. The train data management host includes an on-board computing system and a power module. The on-board computing system is used to perform position signal acquisition, receive and store data from the axle-end data acquisition nodes, identify bearing and wheelset status, train-level network management, remote data transmission, and remote command control. The power module is used to supply power to the on-board computing system. The remote data center system communicates with the train data management host to receive, store, monitor, and manage train wheelset data.

[0008] The signal acquisition system includes: Accelerometer module for collecting vibration acceleration of axle box; Temperature sensing module, used to collect shaft temperature signal of the axle box; Impact sensor module, used to collect impact signals; Speed ​​sensor module, used to collect vehicle speed signals; The main processing module, which is connected to the acceleration sensing module, the temperature sensing module, the impact sensor module, and the velocity sensor module, is used to perform real-time calculations on the data collected by the acceleration sensing module, the temperature sensing module, the impact sensor module, and the velocity sensor module.

[0009] The signal acquisition system also includes a location acquisition module, which is connected to the main processing module and is used to receive geographical location information.

[0010] The edge computing system includes: Audio module, used to acquire audio signals from the shaft end; The video module is used to acquire video data from the shaft end; An edge processor module, connected to the audio module and the video module, is used to calculate temporal feature parameters of the audio signal and extract keyframes from the video data.

[0011] The edge computing system further includes: a data storage module connected to the edge processor module, used to store various sensor signals acquired by the signal acquisition system, audio signals acquired by the audio module, and video data acquired by the video module.

[0012] The vehicle-mounted computing system includes: A geolocation receiving module is used to receive geolocation information; Fieldbus modules are used to form a train-level management network to enable data communication between various onboard computing systems throughout the train. The computing power processor module, which is connected to the geographic location receiving module and the fieldbus module, is used to perform calculation and analysis on the data acquired by the axle-end data acquisition node, realize the identification of wheelset and bearing status, and control the train-level management network.

[0013] The remote data center system includes a server cloud platform, on which monitoring software runs to enable status monitoring, data playback, statistical reports, and fault diagnosis.

[0014] The wheelset condition monitoring and management system includes a communication system, which includes: The communication module installed in the signal acquisition system is connected to the main processing module and is used to realize data communication between the signal acquisition system and the edge computing system. The signal communication module installed in the edge computing system is connected to the edge processor module and is used to realize data communication between the edge computing system and the signal acquisition system. The first communication module installed in the edge computing system is connected to the edge processor module and is used to realize data communication between the edge computing system and the vehicle computing system. The second communication module installed in the vehicle computing system is connected to the computing processor module and is used to realize data communication between the vehicle computing system and the edge computing system. The wireless communication module installed in the vehicle computing system is connected to the computing processor module and is used to realize data communication between the vehicle computing system and the remote data center system. The remote communication module installed in the vehicle-mounted computing system is connected to the computing processor module and is used to realize data communication between the vehicle-mounted computing system and the remote data center system.

[0015] The power module is connected to the train control power supply. The power module includes a 12V switching power supply and a 5V switching power supply. The 12V switching power supply converts the voltage output by the train control power supply into a 12V output voltage. The 5V switching power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply into a 5V output voltage. The computing power processor module is connected to the 5V switching power supply, and the 5V switching power supply provides 5V voltage to the computing power processor module; the second communication module, the geographic location receiving module, the wireless communication module, the fieldbus module, and the remote communication module are connected to the computing power processor module, and the computing power processor module provides 5V voltage to the second communication module, the geographic location receiving module, the wireless communication module, the fieldbus module, and the remote communication module; The signal acquisition system also includes a power conversion and management module, which includes an LDO power supply and a switching power supply. The LDO power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply to a 3.3V output voltage. The switching power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply to a 5V output voltage. The speed sensor module is connected to the 12V switching power supply, and the 12V switching power supply provides 12V voltage to the speed sensor module. The main processing module is connected to the LDO power supply, which provides 3.3V to the main processing module. The acceleration sensing module, the temperature sensor module, the impact sensor module, and the communication module are connected to the main processing module, which provides 3.3V to each of them. The edge processor module is connected to the switching power supply, which provides 5V to the edge processor module. The audio module, the video module, the data storage module, the signal communication module, and the first communication module are connected to the edge processor module. The edge processor module provides 3.3V to the audio module and 5V to the data storage module, the signal communication module, and the first communication module.

[0016] Each train consists of multiple carriages, each carriage has two bogies, each bogie has two axles forming four axle ends, each axle end is equipped with one axle end data acquisition node, and each carriage is equipped with at least two on-board computing systems. The on-site combination of the axle end data acquisition nodes and the on-board computing systems adopts any of the following methods: One-to-one independent: One vehicle-mounted computing power system is matched with one axle-end data acquisition node. Each vehicle-mounted computing power system is independent of each other. Each vehicle-mounted computing power system only manages and controls the data of the axle-end data acquisition node it is matched with. One-to-one master-slave configuration: One onboard computing system is matched with one axle-end data acquisition node, and the onboard computing system manages and controls multiple other onboard computing systems through a train-level management network; One-to-many independent: One onboard computing system processes and manages the data of four axle-end data acquisition nodes on the same bogie that it is matched with; One-to-many master-slave configuration: One onboard computing system processes and manages data from four axle-end data acquisition nodes on the same bogie that it is matched with. One onboard computing system manages and controls multiple other onboard computing systems through a train-level management network.

[0017] The wheelset status monitoring and management system provided by this invention has the following beneficial effects: 1. Significantly Enhanced System Integration and Information Completeness: This invention breaks through the limitations of traditional wheelset monitoring parameters, which are often singular and fragmented, by integrating and collecting multi-dimensional state parameters such as axle box vibration acceleration, bearing temperature, speed, geographical location, noise, impact, and images. It achieves deep integration and unified design of wheelset structure, sensing, information recognition, data interconnection, and applications. The complementarity of multi-source data effectively solves the problem of incomplete fusion diagnostic information, providing a solid data foundation for comprehensive and accurate assessment of wheelset condition.

[0018] 2. Effectively improves the synchronization of multi-sensor data: In response to the problem of poor data synchronization in traditional multi-sensor monitoring systems, this system can uniformly schedule and collaboratively process multi-type sensor data collected from each axis end, ensuring strict temporal and spatial synchronization of heterogeneous data such as vibration, temperature, speed, and images, thereby significantly improving the accuracy of multi-source data fusion analysis and the reliability of fault diagnosis.

[0019] 3. Enhanced Reliability and Stability of Long-Term Monitoring: Through a sophisticated hardware and software architecture design, this invention enables real-time and continuous monitoring of wheelset operating status, and provides remote data visualization and functional display capabilities. Maintenance personnel can remotely and intuitively obtain wheelset health status information, avoiding the shortcomings of traditional monitoring methods that are susceptible to interference and have poor reliability during long-term operation, thus ensuring the long-term stable and effective operation of the monitoring system.

[0020] 4. Imparting intelligent self-sensing and self-identification capabilities to wheelsets: Based on comprehensive sensing and edge computing analysis of multi-dimensional parameters, this invention enables wheelsets to have self-sensing and self-identification functions, promoting the transformation of wheelsets from "passive detection" to "active intelligent early warning", and further improving the guarantee capability of rail transit vehicle operation safety and the level of intelligent operation and maintenance. Attached Figure Description

[0021] Figure 1 This is a structural block diagram of a wheelset condition monitoring and management system provided by the present invention.

[0022] Figure 2 This is a power supply diagram of the power conversion and management module and the power module. Detailed Implementation

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and use non-precise proportions, used only to facilitate and clearly illustrate the embodiments of the present invention. Please refer to the drawings to make the objectives, features, and advantages of the present invention more apparent and understandable. It should be understood that the structures, proportions, sizes, etc., depicted in the accompanying drawings are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the implementation conditions of the present invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in proportions, or adjustments to the size, without affecting the effects and objectives achieved by the present invention, should still fall within the scope of the technical content disclosed in the present invention.

[0024] like Figure 1 As shown, the present invention provides a wheelset condition monitoring and management system, which includes an undercarriage data monitoring unit, a train data management host 2, and a remote data center system 3.

[0025] The undercarriage data monitoring unit includes multiple axle-end data acquisition nodes 1, which are installed on the axle end and are used to collect, calculate and send status data of a single wheelset.

[0026] The train data management host 2 is used to collect the status data of all wheelsets of the entire train sent from all the axle-end data acquisition nodes 1, and to identify and manage the status of wheelsets and bearings.

[0027] The remote data center system 3 is used to receive, store, monitor, and manage train wheelset data.

[0028] This three-level topology not only ensures local data collection, analysis, and control functions, but also effectively realizes data interconnection, communication, and collaborative control between vehicles, trains, and remote control centers.

[0029] Furthermore, the axle-end data acquisition node 1 includes a signal acquisition system 11 and an edge computing system 12. The signal acquisition system 11 is located at the underside of the axle and is used to achieve spatiotemporal synchronous acquisition of acceleration, temperature, impact, and speed signals, as well as power management. The edge computing system 12 is located at the underside of the axle and is used to achieve audio and video acquisition, and spatiotemporal synchronization of audio and video, acceleration, temperature, impact, and speed signals.

[0030] like Figure 1 As shown, the signal acquisition system 11 includes: The acceleration sensing module 111 is used to collect the vibration acceleration of the axle box. It is powered by a 3.3V LDO power supply provided by the power conversion and management module 116 and is connected to the main processing module 117. The temperature sensing module 112 is used to collect the shaft temperature signal of the axle box. It is powered by a 3.3V LDO power supply provided by the power conversion and management module 116 and is connected to the main processing module 117. The impact sensor module 113 is used to collect impact signals. It is powered by a 3.3V LDO power supply provided by the power conversion and management module 116 and is connected to the main processing module 117. In this embodiment, a piezoelectric sensitive impact sensor is selected. The output is a weak charge signal with high internal resistance. It is converted into a voltage signal by a built-in charge amplifier or a high input impedance conditioning circuit. The output is a time-domain electrical signal related to the impact peak value, impact duration, and impact energy.

[0031] The speed sensor module 114 is used to collect vehicle speed signals. It is powered by a 12V switching power supply provided by the power module 22 and is connected to the main processing module 117. In this embodiment, the speed sensor module 114 includes a speed measuring gear and a probe. The communication module 115 is used to realize data communication between the signal acquisition system 11 and the edge computing system 12. It is powered by a 3.3V switching power supply provided by the power conversion and management module 116 and is connected to the main processing module 117. The power conversion and management module 116 is used to power and manage the various modules in the signal acquisition system 11 and the edge computing system 12. It is powered by a 12V switching power supply output from the power module 22 and is connected to the acceleration sensing module 111, the temperature sensing module 112, the impact sensor module 113, the speed sensor module 114, the communication module 115 and the main processing module 117. The main processing module 117 is used to perform real-time calculations (calculation of time-domain characteristic parameters of acceleration signals and threshold matching) and transmission control on the data collected by the acceleration sensing module 111, temperature sensing module 112, impact sensor module 113, and velocity sensor module 114. It is powered by a 3.3V LDO power supply provided by the power conversion and management module 116 and is connected to the acceleration sensing module 111, temperature sensing module 112, impact sensor module 113, velocity sensor module 114 and communication module 115.

[0032] Since the signal acquisition system 11 is mainly used to complete the synchronous acquisition, encoding, and data transmission of acceleration, temperature, impact, and velocity signals, it is required to have real-time computing capabilities. In this embodiment, the main processing module 117 uses a high-performance 32-bit ARM core processor with MCU+DSP+FPU floating-point operation, based on a real-time operating system, and can complete signal acquisition and synchronization within 100µs. Figure 1 As shown, the edge computing system 12 includes: The audio module 121 is used to acquire audio signals from the shaft end. It is powered by a 3.3V LDO power supply provided by the power conversion and management module 116 and is connected to the input / output interface of the edge processor module 126. The video module 122 is used to acquire video data (image of the wheel-rail contact position) at the axle end. It is powered by a 5V switching power supply provided by the power conversion and management module 116 and is connected to the input / output interface of the edge processor module 126. The data storage module 123 is used to store various sensor signals acquired from the signal acquisition system 11, audio signals acquired from the audio module 121, and video data acquired from the video module 122. It is powered by a 5V switching power supply provided by the power conversion and management module 116 and is connected to the edge processor module 126. In this embodiment, the data storage module 123 uses a data cache FLASH. The signal communication module 124 is used to realize data communication between the main processing module 116 in the signal acquisition system 11 and the edge processor module 126 in the edge computing system 12. It is powered by a 5V switching power supply provided by the power conversion and management module 116 and is connected to the edge processor module 126. The first communication module 125 is used to realize data communication between the axle-end data acquisition node 1 and the train data management host 2. It is powered by a 5V switching power supply provided by the power conversion and management module 116 and is connected to the edge processor module 126. The first Wifi near-field communication module 125 is used to transmit data such as acceleration, temperature, impact, speed, position, audio and video collected by the under-vehicle data acquisition node 1 to the on-board computing system 21. The edge processor module 126 is used to calculate the temporal feature parameters of the audio signal, extract key frames from the video data, and control the data transmission between the undercarriage data monitoring unit and the train data management host 2. It is powered by a 5V switching power supply provided by the power conversion and management module 116 and is connected to the audio module 121, video module 122, data storage module 123, signal communication module 124 and the first communication module 125.

[0033] In this embodiment, the edge processor module 126 in the edge computing system 12 adopts a micro high-performance processor and a Linux operating system, which has high reliability.

[0034] like Figure 1 As shown, the train data management host 2 includes an onboard computing system 21 and a power module 22. The onboard computing system 21 is deployed on the train and performs functions such as position signal acquisition, receiving and storing data from the axle-end data acquisition node 1, bearing and wheelset status identification, train-level network management, remote data transmission, and remote command control. The power module 22 is also deployed on the train and is used to supply power to the onboard computing system 21.

[0035] like Figure 1 As shown, the vehicle-mounted computing system 21 includes: The second communication module 211 is used to realize data communication between the axle-end data acquisition node 1 (the first communication module 125 in the edge computing system 12) and the train data management host 2, and is connected to the computing power processor module 216; The geographic location receiving module 212 is used to receive geographic location information and is connected to the computing power processor module 216; in this embodiment, the geographic location receiving module 212 is a GPS module. The wireless communication module 213 is used to realize data communication between the train data management host 2 and the remote data center system 3, and is connected to the computing power processor module 216. The wireless communication module 213 establishes a wireless connection with the trackside base station and uploads the wheelset and bearing status results, multi-sensor feature data, alarm information, compressed audio and video, etc., after being aggregated and processed by the on-board computing power system to the ground base station in real time, and then forwards them to the ground control center or remote cloud platform via the ground network. The fieldbus module 214 is used to form a train-level management network to realize data communication between the various on-board computing power systems 21 of the entire train, and is connected to the computing power processor module 216. The remote communication module 215 is used to realize data communication between the train data management host 2 and the remote data center system 3, and is connected to the computing power processor module 216. The remote communication module 215 is used to realize long-distance wireless data transmission, and transmits the data such as acceleration, temperature, impact, speed, position, audio and video collected by the under-vehicle data acquisition node 1 to the remote data center system 3 after processing by the computing power processor module 216.

[0036] The computing processor module 216 is used to calculate and analyze the data acquired by the axle-end data acquisition node 1, realize the identification of wheelset and bearing status, train-level management network control, and communication control between train-level data management and remote cloud platform. It is powered by the 5V switching power supply of the power supply module 22 and is connected to the second communication module 211, the geographic location receiving module 212, the wireless communication module 213, the fieldbus module 214 and the remote communication module 215.

[0037] In this embodiment, the computing power processor module 216 adopts a micro high-performance processor and a Linux operating system, which has high reliability.

[0038] In this embodiment, both wireless communication module 213 and remote communication module 215 are used to realize data communication between the train data management host 2 and the remote data center system 3, using a redundant communication architecture to improve communication reliability and transmission quality. In other embodiments of the present invention, the signal acquisition system 11 also includes a location acquisition module (not shown in the figure) for receiving geographical location information and is connected to the main processing module 117. The location acquisition module can also be a GPS module. By deploying independent positioning devices (GPS antennas) on and off the train, a redundant positioning architecture is formed, which can significantly improve the reliability of satellite signal reception and the ability to resist obstruction. This achieves high-precision positioning of the axle-end data acquisition node 1 while ensuring that multiple source signals such as acceleration, temperature, impact, speed, and audio / video have unified location markers. At the same time, mutual verification of on-train and off-train positioning information improves the system's fault self-diagnosis capability and data reliability.

[0039] like Figure 1 As shown, the remote data center system 3 includes a server cloud platform 31, on which monitoring software runs. The monitoring software is deployed on the cloud platform of the remote data center and is used to realize status monitoring, data playback, statistical reports, and fault diagnosis.

[0040] like Figure 2As shown, the power module 22 is connected to the train control power supply (typically 110V). The power module 22 includes a 12V switching power supply 221 and a 5V switching power supply 222. The 12V switching power supply 221 converts the voltage output from the train control power supply to a 12V output voltage. The 5V switching power supply 222 is connected to the 12V switching power supply 221 and further converts the voltage output from the 12V switching power supply 221 to a 5V output voltage. The computing power processor module 216 in the onboard computing system 21 is connected to the 5V switching power supply 222, and the output voltage of the 5V switching power supply 222 powers the computing power processor module 216. The computing power processor module 216 then powers the second communication module 211, the geographic location receiving module 212, the wireless communication module 213, the fieldbus module 214, and the remote communication module 215.

[0041] The power conversion and management module 116 in the signal acquisition system 11 includes an LDO power supply 1161 and a switching power supply 1162. The LDO power supply 1161 is connected to the 12V switching power supply 221 in the power module 22, converting the voltage output by the 12V switching power supply 221 to a 3.3V output voltage. The switching power supply 1162 is connected to the 12V switching power supply 221 in the power module 22, converting the voltage output by the 12V switching power supply 221 to a 5V output voltage. The speed sensor module 114 in the signal acquisition system 11 is connected to the 12V switching power supply 221 in the power module 22, and the output voltage of the 12V switching power supply 221 powers the speed sensor module 114. The main processing module 117 in the signal acquisition system 11 is connected to the LDO power supply 1161. The output voltage of the LDO power supply 1161 powers the main processing module 117. The main processing module 117 then powers the acceleration sensing module 111, the temperature sensor module 112 (in this embodiment, a composite sensor of acceleration and temperature signals is selected), the impact sensor module 113, and the communication module 115. The edge processor module 126 in the edge computing system 12 is connected to the switching power supply 1162. The output voltage of the switching power supply 1162 powers the edge processor module 126, which in turn powers the audio module 121, video module 122, data storage module 123, signal communication module 124, and first communication module 125. Specifically, the edge processor module 126 directly provides 5V power to the video module 122, data storage module 123, signal communication module 124, and first communication module 125. The edge processor module 126 converts the 5V power to 3.3V and outputs it to the audio module 121.

[0042] Each train consists of multiple carriages, each carriage has two bogies, each bogie has two axles, forming four axle ends, each axle end is equipped with an axle end data acquisition node 1, and each carriage is equipped with at least two on-board computing systems 21.

[0043] The on-site combination of the axle-end data acquisition node 1 and the on-board computing system 21 in the train data management host 2 can be selected in any of the following ways: 1. One-to-one independent type: One vehicle-mounted computing power system 21 is matched with one axle-end data acquisition node 1. Each vehicle-mounted computing power system 21 is independent of each other. Each vehicle-mounted computing power system 21 only manages and controls the data of the axle-end data acquisition node 1 it is matched with.

[0044] This method offers controllable network transmission and strong real-time performance, but it employs a one-to-one approach between nodes and computing modules, resulting in a large number of computing modules, computing power redundancy, and complex data management.

[0045] 2. One-to-one master-slave configuration: One onboard computing system 21 is matched with one axle-end data acquisition node 1. A train-level management network is also added for the onboard computing system 21, allowing one onboard computing system 21 to manage and control the other multiple onboard computing systems 21. The train-level management network refers to the data communication between the various onboard computing systems 21 of the train via a fieldbus module 214. If a master-slave configuration is adopted, the entire train's wheelset status monitoring and data management can be achieved through this network.

[0046] This approach involves an onboard computing power system node network and a train-level management network. While the master-slave approach makes data management more convenient, the one-to-one relationship between nodes and computing power modules results in a large number of computing power modules and computing power redundancy.

[0047] 3. One-to-many independent type: One on-board computing system 21 performs data processing and management on four axle-end data acquisition nodes 1 on the same bogie that are matched with it.

[0048] This approach uses a one-to-many relationship between nodes and computing modules, making full use of the computing modules, but data management is relatively complex.

[0049] 4. One-to-many master-slave: One onboard computing system 21 processes and manages the data of four axle-end data acquisition nodes 1 on the same bogie that it matches. At the same time, a train-level management network for the onboard computing system 21 is added, so that one onboard computing system 21 can manage and control the other multiple onboard computing systems 21.

[0050] This approach combines the advantages of an onboard computing power system node network and a train-level management network, making data management more convenient through a master-slave architecture; it also utilizes a one-to-many approach between nodes and computing power modules, maximizing the use of the computing power modules.

[0051] The above four combinations can be selected based on a comprehensive consideration of the train's operating environment and cost. These four methods share the following advantages: more convenient remote parameter configuration, larger sample data storage capacity, less data transmission, lower data throughput compared to the axle-end data acquisition node 1 directly communicating with the remote data center system 3, and easier installation of the antenna for the under-vehicle acquisition node.

[0052] Furthermore, the data transmission between the axis-end data acquisition node 1 and the remote data center system 3, namely the communication methods of the communication module 114, the first communication module 125 and the second communication module 211, can all be based on station Wifi or 4G network.

[0053] Furthermore, in the data transmission between the train data management host 2 and the remote data center system 3, the wireless communication module 213 adopts a vehicle-to-ground transmission network, and the remote communication module 215 adopts a 4G network-based communication method.

[0054] Station WiFi networks offer advantages such as lower cost, suitability for closed environments, high bandwidth supporting large-capacity data transmission, strong security, and dedicated network functionality. However, uncontrollable data issues may arise. 4G networks, on the other hand, offer full coverage, support for real-time continuous communication, low latency improving remote control accuracy, flexible deployment without additional infrastructure investment, support for multi-service integration, and easy expansion of intelligent functions. The vehicle-to-ground transmission network is a customized industry-specific wireless communication network for rail transit. It is a private, closed network owned by the rail transit operator, independent of the public network, does not share resources with public users, uses dedicated frequency bands allocated by the state, is free from public network interference, has dedicated spectrum, and offers high security and reliability. In summary, considering deployment flexibility, connection stability, and data transmission efficiency, 4G networks are more practical in most scenarios, especially suitable for remote control requirements requiring continuous coverage and high reliability; while station WiFi has certain advantages in fixed-line, security-sensitive, and cost-sensitive systems. This invention provides optional methods that can be rationally selected based on the actual operating environment of the train.

[0055] To address the issues of low integration in wheelset condition monitoring, poor synchronization of multi-sensor data, incomplete fusion diagnostic information, and poor reliability of long-term monitoring, this invention proposes a wheelset condition monitoring and management system. This system aims to overcome these shortcomings. It collects axle box vibration acceleration, bearing temperature, speed, geographical location, noise, impact, and image status parameters, enabling the wheelset to have self-sensing and self-recognition capabilities. It also provides remote data visualization and functional display, ultimately realizing an integrated intelligent wheelset that combines wheelset structure, sensor perception, information recognition, data interconnection, and applications, achieving real-time monitoring of the wheelset's condition.

[0056] The data collection, storage, and processing involved in this application strictly comply with current laws and regulations. Specifically, all user-related data to be processed in this solution originates from legal channels, and explicit authorization and consent from the data subjects have been obtained through user agreements or privacy policies during the data collection phase. For cases involving sensitive personal information, separate consent from the users has been further obtained, strictly adhering to the principle of informed consent. In the actual data processing process, if identity-identifying information is involved, this solution employs anonymization or de-identification techniques to ensure that the processed data cannot identify any specific natural person and cannot be restored. The data processing activities do not infringe upon personal privacy rights and comply with the provisions of the "Personal Information Protection Law of the People's Republic of China," the "Cybersecurity Law of the People's Republic of China," and other relevant laws. If this solution involves collecting information in public places, the purpose of collection is limited to maintaining public safety or specific scenarios with explicit user authorization, and does not exceed the necessary limits.

[0059] In summary, the technical solution claimed in this application ensures its legality, compliance, and ethics through technical means throughout the entire chain of data acquisition, data processing, and result output, and there is no situation that violates the law, social morality, or harms the public interest.

[0060] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0061] In the description of this invention, it should be understood that the terms "center," "height," "thickness," "upper," "lower," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0062] In the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0063] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0064] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A wheelset condition monitoring and management system, characterized in that, Includes: under-vehicle data monitoring unit, train data management host and remote data center system; The under-vehicle data monitoring unit includes multiple axle-end data acquisition nodes, which are installed on the axle ends and used to collect, calculate, and transmit status data of individual wheelsets. Each axle-end data acquisition node includes a signal acquisition system and an edge computing system. The signal acquisition system is used to realize the spatiotemporal synchronous acquisition of acceleration, temperature, impact, and speed signals and power management. The edge computing system is used to realize audio and video acquisition and the spatiotemporal synchronization of audio and video, acceleration, temperature, impact, and speed signals. The train data management host is deployed on the train and communicates with the axle-end data acquisition nodes. It is used to collect status data of all wheelsets of the entire train sent by all the axle-end data acquisition nodes, and to identify and manage the status of wheelsets and bearings. The train data management host includes an on-board computing system and a power module. The on-board computing system is used to perform position signal acquisition, receive and store data from the axle-end data acquisition nodes, identify bearing and wheelset status, train-level network management, remote data transmission, and remote command control. The power module is used to supply power to the on-board computing system. The remote data center system communicates with the train data management host to receive, store, monitor, and manage train wheelset data.

2. The wheelset condition monitoring and management system as described in claim 1, characterized in that, The signal acquisition system includes: Accelerometer module for collecting vibration acceleration of axle box; Temperature sensing module, used to collect shaft temperature signal of the axle box; Impact sensor module, used to collect impact signals; Speed ​​sensor module, used to collect vehicle speed signals; The main processing module, which is connected to the acceleration sensing module, the temperature sensing module, the impact sensor module, and the velocity sensor module, is used to perform real-time calculations on the data collected by the acceleration sensing module, the temperature sensing module, the impact sensor module, and the velocity sensor module.

3. The wheelset condition monitoring and management system as described in claim 2, characterized in that, The signal acquisition system also includes a location acquisition module, which is connected to the main processing module and is used to receive geographical location information.

4. The wheelset condition monitoring and management system as described in claim 2, characterized in that, The edge computing system includes: Audio module, used to acquire audio signals from the shaft end; The video module is used to acquire video data from the shaft end; An edge processor module, connected to the audio module and the video module, is used to calculate temporal feature parameters of the audio signal and extract keyframes from the video data.

5. The wheelset condition monitoring and management system as described in claim 4, characterized in that, The edge computing system further includes: a data storage module connected to the edge processor module, used to store various sensor signals acquired by the signal acquisition system, audio signals acquired by the audio module, and video data acquired by the video module.

6. The wheelset condition monitoring and management system as described in claim 5, characterized in that, The vehicle-mounted computing system includes: A geolocation receiving module is used to receive geolocation information; Fieldbus modules are used to form a train-level management network to enable data communication between various onboard computing systems throughout the train. The computing power processor module, which is connected to the geographic location receiving module and the fieldbus module, is used to perform calculation and analysis on the data acquired by the axle-end data acquisition node, realize the identification of wheelset and bearing status, and control the train-level management network.

7. The wheelset condition monitoring and management system as described in claim 6, characterized in that, The remote data center system includes a server cloud platform, on which monitoring software runs to enable status monitoring, data playback, statistical reports, and fault diagnosis.

8. The wheelset condition monitoring and management system as described in claim 7, characterized in that, The wheelset condition monitoring and management system includes a communication system, which includes: The communication module installed in the signal acquisition system is connected to the main processing module and is used to realize data communication between the signal acquisition system and the edge computing system. The signal communication module installed in the edge computing system is connected to the edge processor module and is used to realize data communication between the edge computing system and the signal acquisition system. The first communication module installed in the edge computing system is connected to the edge processor module and is used to realize data communication between the edge computing system and the vehicle computing system. The second communication module installed in the vehicle computing system is connected to the computing processor module and is used to realize data communication between the vehicle computing system and the edge computing system. The wireless communication module installed in the vehicle computing system is connected to the computing processor module and is used to realize data communication between the vehicle computing system and the remote data center system. The remote communication module installed in the vehicle-mounted computing system is connected to the computing processor module and is used to realize data communication between the vehicle-mounted computing system and the remote data center system.

9. The wheelset condition monitoring and management system as described in claim 8, characterized in that, The power module is connected to the train control power supply. The power module includes a 12V switching power supply and a 5V switching power supply. The 12V switching power supply converts the voltage output by the train control power supply into a 12V output voltage. The 5V switching power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply into a 5V output voltage. The computing power processor module is connected to the 5V switching power supply, and the 5V switching power supply provides 5V voltage to the computing power processor module; the second communication module, the geographic location receiving module, the wireless communication module, the fieldbus module, and the remote communication module are connected to the computing power processor module, and the computing power processor module provides 5V voltage to the second communication module, the geographic location receiving module, the wireless communication module, the fieldbus module, and the remote communication module; The signal acquisition system also includes a power conversion and management module, which includes an LDO power supply and a switching power supply. The LDO power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply to a 3.3V output voltage. The switching power supply is connected to the 12V switching power supply and converts the voltage output by the 12V switching power supply to a 5V output voltage. The speed sensor module is connected to the 12V switching power supply, and the 12V switching power supply provides 12V voltage to the speed sensor module. The main processing module is connected to the LDO power supply, which provides 3.3V to the main processing module. The acceleration sensing module, the temperature sensor module, the impact sensor module, and the communication module are connected to the main processing module, which provides 3.3V to each of them. The edge processor module is connected to the switching power supply, which provides 5V to the edge processor module. The audio module, the video module, the data storage module, the signal communication module, and the first communication module are connected to the edge processor module. The edge processor module provides 3.3V to the audio module and 5V to the data storage module, the signal communication module, and the first communication module.

10. The wheelset condition monitoring and management system as described in claim 9, characterized in that, Each train consists of multiple carriages, each carriage has two bogies, each bogie has two axles forming four axle ends, each axle end is equipped with one axle end data acquisition node, and each carriage is equipped with at least two on-board computing systems. The on-site combination of the axle end data acquisition nodes and the on-board computing systems adopts any of the following methods: One-to-one independent: One vehicle-mounted computing power system is matched with one axle-end data acquisition node. Each vehicle-mounted computing power system is independent of each other. Each vehicle-mounted computing power system only manages and controls the data of the axle-end data acquisition node it is matched with. One-to-one master-slave configuration: One onboard computing system is matched with one axle-end data acquisition node, and the onboard computing system manages and controls multiple other onboard computing systems through a train-level management network; One-to-many independent: One onboard computing system processes and manages the data of four axle-end data acquisition nodes on the same bogie that it is matched with; One-to-many master-slave configuration: One onboard computing system processes and manages data from four axle-end data acquisition nodes on the same bogie that it is matched with. One onboard computing system manages and controls multiple other onboard computing systems through a train-level management network.

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