Anti-derailing device and method

Abstract

The invention discloses an anti-derailment device and method, and belongs to the technical field of railway traffic safety, the device comprises an integration box, a counterweight assembly and a moving assembly, an edge calculation unit is arranged in the integration box, the counterweight assembly is integrated in the integration box, and the edge calculation unit is connected with the edge calculation unit. The integration box is fixedly arranged above the moving assembly based on a hanging piece at the top, a hydraulic device and a damper are arranged on the moving assembly, and the hydraulic device is used for adjusting the damping coefficient of the damper; firstly, comprehensive acquisition and preprocessing of vehicle-mounted and rail-side double-end data are completed through cooperation of an edge calculation unit and a central control unit, secondly, the central control unit integrates the data and divides the data into four levels of risk levels, and then parameter adaptation and safety monitoring are carried out on a motor and a hydraulic device through the central control unit. And finally, an edge calculation unit controls a counterweight assembly to adjust the gravity center, a hydraulic device drives a damper to suppress vibration, efficient cooperation of active intervention and passive protection is formed, and automatic precise intervention is achieved.

Description

Technical Field

[0001] This invention relates to the field of railway traffic safety technology, specifically to an anti-derailment device and method. Background Technology

[0002] Currently, the mainstream derailment prevention technologies in the railway field mainly include three categories: trackside monitoring and protection technology, train-mounted monitoring technology, and passive protection structures. Trackside monitoring and protection technology mostly collects track status data by setting sensors at track-related components and triggers warnings when thresholds are exceeded. However, it can only achieve environmental monitoring and cannot directly intervene on the train itself. Train-mounted monitoring technology relies on various sensors on the bogie to monitor the wheel-rail contact status. After detecting anomalies, it mostly prompts the driver to slow down, which relies too much on manual response and lacks automated and precise active adjustment mechanisms. Passive protection structures, as the last physical barrier, can only passively block the train when it shows signs of derailment, and cannot predict and mitigate risks in advance. Even some existing technologies that attempt to combine on-board monitoring and trackside passive protection can only achieve a simple combination of "warning + passive blocking" and lack coordinated linkage between core control units. Existing technologies generally suffer from problems such as a disconnect between data collection and intervention execution, an inability to accurately adapt parameters to the executing agency after risk assessment, and a lack of efficient coordination between proactive intervention and passive protection. This results in protection either remaining at the early warning level with a delayed response and insufficient accuracy, or passive protection lagging behind the development of risks, making it difficult to dynamically adjust the intervention intensity according to the real-time risk level. It is impossible to achieve accurate, rapid, and coordinated resolution of different levels of derailment risks across the entire chain, and it cannot meet the timeliness, accuracy, and coordination requirements for derailment prevention and protection during train operation, thus creating protection loopholes and safety hazards. Summary of the Invention

[0003] To address the problems mentioned in the background section, the present invention provides an anti-derailment device and method, the technical solution of which is as follows:

[0004] A derailment prevention device and method, implemented based on the derailment prevention device, the device including a central control unit and an edge computing unit, including the following steps:

[0005] S10: The edge computing unit acquires data collected by the level and speed sensors and transmits it to the central control unit as vehicle monitoring data. The central control unit acquires track monitoring data in real time based on a differentiated acquisition strategy.

[0006] S20: The central control unit integrates on-board monitoring data and track monitoring data, compares them with the preset four-level derailment risk level, and sends the generated risk level information to the edge computing unit;

[0007] S30: After issuing risk level information, the central control unit relies on the preset intelligent matching algorithm to synchronously and collaboratively control the servo motor and hydraulic device to complete parameter adaptation and safety monitoring before intervention.

[0008] S40: The edge computing unit adjusts the bogie's center of gravity by controlling the adapted servo motor to adjust the counterweights based on the risk level information, and adjusts the damper state by controlling the hydraulic device. Finally, it evaluates the intervention effect and makes dynamic adjustments through dual-end monitoring.

[0009] Preferably, step S10 includes the following steps:

[0010] S101: The edge computing unit acquires the train's horizontal status and speed parameters collected by the level gauge and speed sensor according to the corresponding cycle, and obtains the raw monitoring data;

[0011] S102: The edge computing unit filters, reduces noise, and standardizes the collected raw detection data before generating vehicle monitoring data and transmitting it to the central control unit.

[0012] S103: The central control unit, based on a differentiated acquisition strategy, synchronously acquires track monitoring data collected by the track-side monitoring module according to the corresponding cycle.

[0013] As a preferred embodiment, S201: The central control unit receives the vehicle monitoring data transmitted by the edge computing unit and simultaneously collects the track monitoring data;

[0014] S202: The central control unit integrates and extracts features from the on-board monitoring data and track monitoring data, generates multimodal correlation information, and classifies the current operating status into risks based on preset risk assessment rules to obtain derailment risk level information;

[0015] S203: The central control unit sends the divided derailment risk level information to the edge computing unit;

[0016] S204: The edge computing unit receives risk level information and calls the preset risk level response strategy.

[0017] Preferably, in step S204, the derailment risk level includes four levels: no risk, low risk, medium risk, and high risk. The corresponding strategies for each risk level are as follows:

[0018] When there is no risk: the edge computing unit controls each monitoring device to maintain routine data acquisition and inspection, while the central control unit only monitors the basic parameters of the motor and hydraulic system;

[0019] When the risk is low, the edge computing unit pushes warning prompts to the driver through the vehicle terminal and provides voice reminders to pay attention to key indicators;

[0020] In cases of moderate risk, the edge computing unit triggers an active intervention command to control the servo motor and hydraulic system to correct the lateral movement of the wheelsets and the tilting posture of the bogie, and simultaneously sends a deceleration suggestion to the driver;

[0021] In cases of high risk, the edge computing unit works in conjunction with the train braking coordination unit to perform graded braking, while simultaneously sending a signal to the trackside control system to put the passive protection module into standby mode.

[0022] Preferably, step S30 includes the following steps:

[0023] S301: After issuing risk level information, the central control unit establishes a dynamic correlation model between motor output torque and hydraulic circuit pressure based on a preset intelligent matching algorithm.

[0024] S302: The central control unit uses a dynamic correlation model to precisely match the power output of the servo motor and the oil pressure and flow of the hydraulic device, ensuring that the two actions respond synchronously to the risk level requirements.

[0025] S303: Based on redundant sensor monitoring groups, the servo motor speed and hydraulic device oil temperature are monitored and verified in real time through dual channels.

[0026] Preferably, step S40 includes the following steps:

[0027] S401: The edge computing unit, based on the adapted servo motor and hydraulic device, controls the servo motor to adjust the counterweight according to the risk level information, thereby changing the bogie counterweight distribution to adjust the center of gravity.

[0028] S402: The edge computing unit synchronously controls the hydraulic device to drive the damper, thereby adjusting the damping coefficient and the extension stroke;

[0029] S403: The on-board and trackside monitoring modules synchronously acquire optimized operation data after intervention and transmit it to the edge computing unit;

[0030] S404: The edge computing unit performs feature comparison and trend analysis on the intervention effect based on optimized operation data, and feeds back the generated analysis results to the central control unit;

[0031] S405: If the risk level is reduced to no risk or low risk, the active intervention will be gradually lifted in stages according to the preset sequence; if the risk is not reduced or is upgraded, an enhanced intervention command will be triggered to continuously adjust the adjustment range of the counterweight and the damping state of the damper until the risk is controllable.

[0032] An anti-derailment device is applied to an anti-derailment method, comprising an integrated box, a counterweight assembly, and a moving assembly. An edge computing unit is provided inside the integrated box. The counterweight assembly is integrated inside the integrated box. The integrated box is fixed above the moving assembly based on a top suspension component. The moving assembly is provided with a hydraulic device and a damper. The hydraulic device is used to adjust the damping coefficient of the damper.

[0033] Preferably, two counterweight components are symmetrically arranged inside the integrated box. Each counterweight component includes a servo motor, a counterweight rope, a fixed pulley, and a counterweight piece. The servo motor is fixedly installed inside the integrated box. The servo motor is fixedly connected to the counterweight piece after the counterweight rope passes over the fixed pulley. The counterweight piece is divided into multiple parts connected in series on the counterweight rope.

[0034] Preferably, the moving component includes two traveling wheels connected by a connecting shaft. Each traveling wheel is provided with a limiting component on both sides to prevent derailment. The top of each limiting component is also fixedly mounted with a corresponding hydraulic device, and the hydraulic rods of the hydraulic devices on both sides are fixedly connected to dampers.

[0035] The beneficial effects of the anti-derailment device and method of the present invention are as follows:

[0036] This invention utilizes a collaborative approach between an edge computing unit and a central control unit to comprehensively collect and preprocess data from both the vehicle and trackside, ensuring data integrity and accuracy and avoiding judgment biases caused by single-dimensional data. The central control unit then integrates the data to classify it into four risk levels, replacing the existing crude risk assessment model and providing a scientific basis for differentiated intervention. Subsequently, the central control unit performs parameter adaptation and safety monitoring of the motor and hydraulic devices, resolving the hidden dangers of uncoordinated actions and malfunctions in existing actuators, ensuring intervention safety. Next, the edge computing unit controls the counterweight component to adjust the center of gravity, and the hydraulic device drives the damper to suppress vibration. Combined with the passive protection of the moving components, this forms a highly efficient combination of active intervention and passive protection, replacing the inefficient method of relying on manual deceleration or simple passive blocking, achieving automated and precise intervention. Finally, through closed-loop feedback from dual-end monitoring, the intervention strategy is dynamically adjusted, avoiding the shortcomings of existing technologies that lack feedback and cannot adapt to changes in risk, ensuring continuous optimization of the intervention effect. The entire process does not require excessive reliance on manual labor, forming a collaborative linkage from data to execution, comprehensively improving the timeliness, accuracy, and reliability of derailment prevention and protection. Attached Figure Description

[0037] Figure 1 This is a schematic flowchart illustrating an embodiment of an anti-derailment device and method according to this application;

[0038] Figure 2 This is a schematic diagram of the implementation process of step S10 in an embodiment of an anti-derailment device and method of this application;

[0039] Figure 3 This is a schematic diagram of the implementation process of step S20 in an embodiment of an anti-derailment device and method of this application;

[0040] Figure 4 This is a schematic diagram of the implementation process of step S30 in an embodiment of an anti-derailment device and method of this application;

[0041] Figure 5 This is a schematic diagram of the implementation process of step S40 in an embodiment of an anti-derailment device and method of this application;

[0042] Figure 6 This is a cross-sectional view of the anti-derailment device in an embodiment of the anti-derailment device and method of this application.

[0043] Among them, 1. Integrated box; 2. Counterweight assembly; 3. Moving assembly; 101. Edge computing unit; 102. Suspension component; 201. Servo motor; 202. Counterweight rope; 203. Fixed pulley; 204. Counterweight component; 301. Hydraulic device; 302. Hydraulic rod; 303. Damper; 304. Traveling wheel; 305. Connecting shaft; 306. Limiting assembly. Detailed Implementation

[0044] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] As attached Figure 1-5 As shown, an anti-derailment method is implemented based on an anti-derailment device, which includes a central control unit and an edge computing unit, and includes the following steps:

[0046] S10: The edge computing unit acquires data collected by the level and speed sensors and transmits it to the central control unit as vehicle monitoring data. The central control unit acquires track monitoring data in real time based on a differentiated acquisition strategy.

[0047] S20: The central control unit integrates on-board monitoring data and track monitoring data, compares them with the preset four-level derailment risk level, and sends the generated risk level information to the edge computing unit;

[0048] S30: After issuing risk level information, the central control unit relies on the preset intelligent matching algorithm to synchronously and collaboratively control the servo motor and hydraulic device to complete parameter adaptation and safety monitoring before intervention.

[0049] S40: The edge computing unit adjusts the bogie's center of gravity by controlling the adapted servo motor to adjust the counterweights based on the risk level information, and adjusts the damper state by controlling the hydraulic device. Finally, it evaluates the intervention effect and makes dynamic adjustments through dual-end monitoring.

[0050] In this embodiment, the derailment prevention method is based on a derailment prevention device comprising a central control unit and an edge computing unit. The steps are logically interconnected and progressively advanced: S10 First, the edge computing unit acquires core parameters such as the train's level status and speed collected by the onboard level gauge and speed sensor. After processing, these parameters are transmitted to the central control unit as onboard monitoring data. Simultaneously, the central control unit acquires track monitoring data based on differentiated acquisition strategies (such as high-frequency acquisition at the onboard end and track-side adaptation periodic acquisition), achieving comprehensive coverage of data from both ends and providing a complete data foundation for subsequent risk assessment; S20 The central control unit deeply integrates the two types of data, combining bogie attitude, wheel-rail interaction force, and other related information to complete a four-level risk classification, and then sends the level information to the edge computing unit to clarify the intervention direction; S30 As a key connecting step, the central control unit establishes a dynamic correlation model between the motor and hydraulic device based on a preset algorithm, completing precise parameter adaptation and equipment safety monitoring before intervention, avoiding uncoordinated actions or faulty operation of the actuators; S40 Based on the adapted equipment, the edge computing unit controls the release or retraction of the weight-adding plates to adjust the center of gravity and drive the damper to adjust its state according to the risk level. Then, through dual-end monitoring, a closed-loop feedback is formed to dynamically optimize intervention measures. The entire process realizes a full-chain anti-derailment protection of "data collection - risk assessment - parameter adaptation - precise intervention - effect feedback", ensuring that each link can accurately respond to the train's operating status.

[0051] In one embodiment, step S10 includes the following steps:

[0052] S101: The edge computing unit acquires the train's horizontal status and speed parameters collected by the level gauge and speed sensor according to the corresponding cycle, and obtains the raw monitoring data;

[0053] S102: The edge computing unit filters, reduces noise, and standardizes the collected raw detection data before generating vehicle monitoring data and transmitting it to the central control unit.

[0054] S103: The central control unit, based on a differentiated acquisition strategy, synchronously acquires track monitoring data collected by the track-side monitoring module according to the corresponding cycle.

[0055] In this embodiment, the core of step S10 is to complete the collection, preprocessing, and aggregation of the basic data required for derailment risk assessment. After the monitoring module is started in S101, the edge computing unit accurately acquires the horizontal state parameters such as the train tilt angle and sway amplitude collected by the on-board level instrument, as well as the real-time driving speed data collected by the speed sensor according to the corresponding cycle, ensuring that no key operating data of the on-board end is missed. In S102, the edge computing unit performs targeted preprocessing on the collected raw data. Through filtering, it filters out instantaneous invalid signals such as track irregularities and electromagnetic interference. Noise reduction processing eliminates the electronic noise of the sensor itself. Standardization processing unifies and standardizes raw data of different formats and magnitudes (such as converting speed and angle data into analysis indicators of the same magnitude), which greatly improves data quality and avoids invalid data interfering with subsequent decisions. In S103, based on the differentiated acquisition strategy, the central control unit synchronously acquires track monitoring data such as track geometry and contact stress collected by the track-side monitoring module according to the adaptation cycle, and completes the preliminary aggregation of data from both the on-board and track ends. This lays a solid foundation for the multi-source data integration and analysis in S20, ensuring that the risk assessment can take into account both the train's own state and the influence of the track environment.

[0056] In one embodiment, step S20 includes the following steps:

[0057] S201: The central control unit receives the vehicle monitoring data transmitted by the edge computing unit and simultaneously collects the track monitoring data;

[0058] S202: The central control unit integrates and extracts features from the on-board monitoring data and track monitoring data, generates multimodal correlation information, and classifies the current operating status into risks based on preset risk assessment rules to obtain derailment risk level information;

[0059] S203: The central control unit sends the divided derailment risk level information to the edge computing unit;

[0060] S204: The edge computing unit receives risk level information and calls the preset risk level response strategy.

[0061] In this embodiment, step S20 focuses on data integration, risk classification, and response strategy invocation, which is the core of achieving differentiated protection: S201 The central control unit first synchronously receives the preprocessed on-board monitoring data transmitted by the edge computing unit, as well as the collected track monitoring data, to ensure that both types of key data are fully included in the analysis; S202 The central control unit deeply integrates the dual-end data, combining the bogie attitude offset, wheel-rail contact pressure distribution, track smoothness, and other related information, and through feature extraction, filters out key features directly related to derailment risk (such as abnormal fluctuations in wheel-rail force, train tilting trend, etc.) from massive data, and uses threshold dynamic matching (dynamically adjusting the judgment threshold according to train speed and track type) and trend inference (predicting the direction of risk development, such as whether the tilt will continue to worsen) to accurately classify derailment risk into four levels: no risk, low risk, medium risk, and high risk, ensuring the scientific and refined nature of risk judgment; S203 The central control unit sends the risk level information after classification to the edge computing unit in real time to clarify the direction of subsequent processing. After receiving the risk level information, the S204 edge computing unit immediately calls the preset risk level response strategy to prepare for subsequent execution. This forms a dual guarantee of active intervention and passive protection to minimize the risk of derailment.

[0062] In one embodiment, in step S204, the derailment risk level includes four levels: no risk, low risk, medium risk, and high risk. The corresponding strategy for each risk level is as follows:

[0063] When there is no risk: the edge computing unit controls each monitoring device to maintain routine data acquisition and inspection, while the central control unit only monitors the basic parameters of the motor and hydraulic system;

[0064] When the risk is low, the edge computing unit pushes warning prompts to the driver through the vehicle terminal and provides voice reminders to pay attention to key indicators;

[0065] In cases of moderate risk, the edge computing unit triggers an active intervention command to control the servo motor and hydraulic system to correct the lateral movement of the wheelsets and the tilting posture of the bogie, and simultaneously sends a deceleration suggestion to the driver;

[0066] In cases of high risk, the edge computing unit works in conjunction with the train braking coordination unit to perform graded braking, while simultaneously sending a signal to the trackside control system to put the passive protection module into standby mode.

[0067] In this embodiment, under no-risk conditions, the edge computing unit controls each monitoring device to maintain routine data acquisition and equipment inspection at a reasonable frequency. The central control unit only monitors basic parameters such as voltage and oil pressure of the motor and hydraulic system, ensuring safety without affecting the normal operation efficiency of the train. Under low-risk conditions, the edge computing unit pushes precise early warning prompts to the driver through the on-board terminal, including abnormal parameter types (such as speed fluctuations, slight tilt) and related components (such as a bogie). At the same time, it reminds the driver in voice form to pay close attention to the changing trends of key indicators such as bogie vibration amplitude and wheelset displacement, allowing the driver to be aware of abnormal situations in advance and make corresponding preparations. In the case of moderate risk, the edge computing unit triggers an active intervention command, controlling the bogie attitude adjustment hydraulic unit to correct the wheelset lateral movement and frame tilt in a smooth adjustment manner, and simultaneously issues a clear deceleration suggestion to the driver (such as reducing to the current safe speed range) to quickly resolve potential risks. In the case of high risk, the edge computing unit and the train braking coordination unit work together to implement a graded braking strategy of first smooth and then intensified braking, and at the same time send a linkage signal to the track side, so that passive protection modules such as emergency wheel stoppers and anti-derailment guards can enter a standby state in a short time, forming a dual guarantee of active intervention and passive protection to minimize the risk of derailment.

[0068] In one embodiment, step S30 includes the following steps:

[0069] S301: After issuing risk level information, the central control unit establishes a dynamic correlation model between motor output torque and hydraulic circuit pressure based on a preset intelligent matching algorithm.

[0070] S302: The central control unit uses a dynamic correlation model to precisely match the power output of the servo motor and the oil pressure and flow of the hydraulic device, ensuring that the two actions respond synchronously to the risk level requirements.

[0071] S303: Based on redundant sensor monitoring groups, the servo motor speed and hydraulic device oil temperature are monitored and verified in real time through dual channels.

[0072] In this embodiment, step S30 is a crucial link between risk level determination and active intervention execution. Its core function is to ensure the accuracy and safety of the intervention action: In S301, after the central control unit sends the risk level information to the edge computing unit, it immediately establishes a dynamic correlation model between the motor output torque and the hydraulic circuit pressure based on a preset intelligent matching algorithm. This model can calculate the optimal matching parameters between the two in real time according to the intervention requirements of different risk levels (such as moderate risk requiring gentle attitude adjustment and high risk requiring strong and stable state); In S302, based on this model, the power output of the motor drive module and the oil pressure and flow rate of the hydraulic actuator are precisely matched simultaneously to ensure that the motor (controlling the center of gravity adjustment) and the hydraulic device (controlling the damping adjustment) move synchronously and match in force, avoiding single If the device moves too quickly or with improper force, it can cause the train to lose its balance. For example, under high-risk conditions, the rapid adjustment of the counterweight by the motor and the increase of damping by the hydraulic device must be carried out simultaneously to quickly stabilize the train's state. The S303 uses a redundant sensor monitoring group to perform dual-channel parallel monitoring and data verification of key operating parameters such as motor speed and hydraulic oil temperature. Dual-channel monitoring can avoid monitoring failure caused by the failure of a single sensor, and data verification can eliminate abnormal monitoring data (such as instantaneous false alarms from sensors) to ensure that the monitoring results are true and reliable. When any parameter exceeds the preset safety threshold (such as excessive motor speed or excessive hydraulic oil temperature), the system automatically triggers a graded protective shutdown mechanism, which prioritizes cutting off power output and locking the actuator to prevent the equipment failure from escalating and causing secondary risks, thus providing a safe and reliable equipment foundation for subsequent precise intervention.

[0073] In one embodiment, step S40 includes the following steps:

[0074] S401: The edge computing unit, based on the adapted servo motor and hydraulic device, controls the servo motor to adjust the counterweight according to the risk level information, thereby changing the bogie counterweight distribution to adjust the center of gravity.

[0075] S402: The edge computing unit synchronously controls the hydraulic device to drive the damper, thereby adjusting the damping coefficient and the extension stroke;

[0076] S403: The on-board and trackside monitoring modules synchronously acquire optimized operation data after intervention and transmit it to the edge computing unit;

[0077] S404: The edge computing unit performs feature comparison and trend analysis on the intervention effect based on optimized operation data, and feeds back the generated analysis results to the central control unit;

[0078] S405: If the risk level is reduced to no risk or low risk, the active intervention will be gradually lifted in stages according to the preset sequence; if the risk is not reduced or is upgraded, an enhanced intervention command will be triggered to continuously adjust the adjustment range of the counterweight and the damping state of the damper until the risk is controllable.

[0079] In this embodiment, step S40 is the core link of active intervention execution and effect closed-loop feedback, relying on the equipment adapted by S30 to achieve efficient protection: S401 The edge computing unit accurately controls the servo motor to release or retract the weight-adding plates according to the risk level information issued by the central control unit. By changing the distribution position of the weight-adding plates (such as moving them to the side with insufficient force), the weight distribution of the bogie is adjusted, thereby optimizing the position of the train's center of gravity and reducing the problem of uneven wheel-rail force; S402 At the same time, the hydraulic device drives the damper to achieve stepless adjustment of the damping coefficient and extension stroke, specifically suppressing the vibration and impact of the bogie (such as increasing damping when running at high speed and decreasing damping when bumping at low speed); S403 The on-board monitoring module focuses on collecting data such as wheelset attitude and wheel-rail force after intervention, while the track-side monitoring module simultaneously collects data such as track contact stress and geometric state. The data from both ends are transmitted synchronously to Edge computing units ensure comprehensive monitoring of intervention effects. The S404 edge computing unit performs feature comparison (comparing with abnormal features during risk level determination) and trend analysis (determining whether the risk has been mitigated) on the collected data, and feeds back the analysis results to the central control unit in real time, forming a closed loop. If the feedback shows that the risk level has decreased to no risk or low risk, the system gradually removes the active intervention in stages according to the preset sequence of "first smoothly lowering the damping coefficient, then gradually resetting the counterweight position," with reasonable intervals (such as hundreds of milliseconds) set for each stage, to avoid sudden withdrawal of intervention measures causing a change in train attitude and secondary disturbances. If the risk level has not decreased or has even increased, an enhanced intervention command is immediately triggered, appropriately increasing the release or retraction amplitude of the weight-adding plates and the adjustment of the damping coefficient, continuously cyclically adjusting until the risk falls back to a controllable range, ensuring the continuous effectiveness of the intervention and guaranteeing the safety of train operation throughout the process.

[0080] As attached Figure 6 As shown, an anti-derailment device is applied to an anti-derailment method, including an integrated box 1, a counterweight component 2, and a moving component 3. An edge computing unit 101 is provided inside the integrated box 1. The counterweight component 2 is integrated inside the integrated box 1. The integrated box 1 is fixedly installed above the moving component 3 based on a top suspension component 102. The moving component 3 is provided with a hydraulic device 301 and a damper 303. The hydraulic device 301 is used to adjust the damping coefficient of the damper 303.

[0081] In this embodiment, the device consists of an integrated box 1, a counterweight component 2, and a moving component 3. The counterweight component 2 is integrated inside the integrated box 1, which ensures the sealing and safety of the counterweight adjustment mechanism, prevents environmental factors such as vibration and dust from affecting the performance of components during train operation, and allows for centralized management of counterweight adjustment-related components, simplifying the transmission path. The integrated box 1 is fixed above the moving component 3 by a top suspension member 102. This suspension design provides ample space for the movement of the counterweight component 2, ensuring no mechanical interference when the counterweight 204 is released or retracted. At the same time, it maintains a relatively stable positional relationship between the integrated box 1 and the moving component 3, laying a structural foundation for the accuracy of center of gravity adjustment. The mobile component 3 serves as the support and moving foundation of the device. The hydraulic device 301 and damper 303 mounted on it form a damping adjustment unit. The hydraulic device 301 can precisely adjust the damping coefficient of the damper 303 by receiving control commands from the edge computing unit 101, adapting to the vibration suppression requirements under different risk levels. Together with the counterweight component 2 in the integrated box 1, it forms a dual intervention mechanism of "center of gravity adjustment + vibration suppression", perfectly matching the core logic of "coordinated control and precise intervention" in the anti-derailment method, ensuring that the device can efficiently respond to the commands of the central control unit and the edge computing unit 101, and achieve rapid resolution of derailment risk.

[0082] In one embodiment, two counterweight components 2 are symmetrically arranged inside the integrated box 1. Each counterweight component 2 includes a servo motor 201, a counterweight rope 202, a fixed pulley 203, and a counterweight 204. The servo motor 201 is fixedly installed inside the integrated box 1. The servo motor 201 is fixedly connected to the counterweight 204 after the counterweight rope 202 passes over the fixed pulley 203. The counterweight 204 is divided into multiple parts connected in series on the counterweight rope 202.

[0083] In this embodiment, two counterweight components 2 are symmetrically arranged inside the integrated box 1. This symmetrical layout ensures that the counterweight adjustment on both sides of the bogie is balanced and controllable, avoiding posture imbalance caused by unilateral adjustment. At the same time, the coordinated action of the components on both sides can expand the range of center of gravity adjustment, adapting to different tilting and offset scenarios of the train. Each counterweight component 2 consists of a servo motor 201, a counterweight rope 202, a fixed pulley 203, and a counterweight 204. The servo motor 201 is fixedly installed inside the integrated box 1 to ensure the stability of power output. As the power source for counterweight adjustment, it can precisely control the speed and direction according to the instructions of the edge computing unit 101, thereby realizing the release or retrieval of the counterweight rope 202. The fixed pulley 203 plays the role of changing the direction of force and optimizing the transmission path in the component, so that the power of the servo motor 201 can be efficiently transmitted to the counterweight 204, avoiding problems such as entanglement and friction of the counterweight rope 202 during transmission, and ensuring the smoothness of the adjustment process. The counterweight 204 adopts a multi-part series structure design, which can realize precise control of counterweight adjustment. For example, when the train only needs to slightly adjust the center of gravity, part of the counterweight 204 can be released or retrieved. When the risk level is high and a large adjustment is required, the action of all counterweight 204 can be controlled in a coordinated manner. This design not only improves the flexibility of counterweight adjustment, but also accurately matches the center of gravity adjustment requirements under different risk levels in the anti-derailment method, ensuring the optimized effect of bogie counterweight distribution.

[0084] In one embodiment, the moving component 3 includes two traveling wheels 304 connected by a connecting shaft 305. Each traveling wheel 304 is provided with a limiting component 306 on both sides to prevent derailment. The top of each limiting component 306 is also fixedly mounted with a corresponding hydraulic device 301. The hydraulic rods 302 of the hydraulic devices 301 on both sides are fixedly connected to a damper 303.

[0085] In this embodiment, the moving component 3 connects two traveling wheels 304 via a connecting shaft 305, forming a stable load-bearing and moving structure. This allows the device to move synchronously with the train bogie, ensuring that the center of gravity adjustment and damping intervention always conform to the train's operating state. Limiting components 306, located on both sides of the traveling wheels 304, serve as the first passive protective barrier of the device. They can initially block slight wheelset misalignment or lateral movement, preventing further derailment and complementing the active intervention mechanism. Symmetrically mounted hydraulic devices 301 are mounted on the top of the limiting components 306. This arrangement allows for a more balanced force exerted by the hydraulic devices 301 on the damper 303, ensuring precise and controllable adjustment of the damper 303's extension and contraction stroke and damping coefficient, and preventing damping adjustment failure due to uneven force. The hydraulic rod 302 of the hydraulic device 301 is directly fixedly connected to the damper 303. This rigid connection reduces power transmission loss and allows the hydraulic device 301 to respond quickly to the damper 303, enabling real-time adjustment of the damping state. This perfectly matches the "real-time coupling and coordination" control requirements in the anti-derailment method. The structural design of the entire moving component 3 ensures both the mobility and operational stability of the device. Through the coordination of the limiting component 306 and the hydraulic-damping unit, it forms a combined structure of "passive protection + active damping adjustment." Together with the counterweight component 2 in the integrated box 1, it constructs a comprehensive and multi-layered anti-derailment protection system.

[0086] The specific implementation process of the anti-derailment device and method of the present invention is as follows:

[0087] First, during the data acquisition phase, the edge computing unit 101 acquires the train's own operating parameters collected by the onboard level and speed sensors. After filtering, noise reduction, and standardization preprocessing, these parameters are transmitted to the central control unit as onboard monitoring data. Simultaneously, the central control unit acquires track-side monitoring data based on a differentiated acquisition strategy, achieving comprehensive coverage of both the train's own status and track environment data, providing complete and high-quality data support for risk assessment. Subsequently, the central control unit deeply integrates the dual-end data, combining bogie attitude, wheel-rail interaction forces, and other related information. Through feature extraction, dynamic threshold matching, and trend extrapolation, it accurately classifies derailment risks into four levels and sends this level information to the edge computing unit 101, clarifying the subsequent intervention direction. As a crucial connecting link, the central control unit establishes a dynamic correlation model between motor output torque and hydraulic circuit pressure based on a preset algorithm. This allows for precise parameter adaptation of the motor drive module and hydraulic actuator before intervention. Simultaneously, redundant sensors with dual channels monitor and verify equipment status, eliminating potential faults and ensuring the safety and coordination of intervention actions. Finally, based on the adapted actuator, the edge computing unit 101 controls the servo motor 201 to release or retract the weight-adding plates according to different risk levels to adjust the bogie's center of gravity, and synchronously drives the damper 303 to adjust the damping coefficient and extension stroke, thereby achieving targeted active intervention. At the same time, the on-board and trackside monitoring modules continuously collect data after intervention, transmit it to the edge computing unit 101 for effect analysis, and feed it back to the central control unit to dynamically adjust the intervention intensity or remove the intervention step by step, forming a closed-loop protection, and achieving precise, rapid, and dynamic mitigation of derailment risks throughout the entire process.

[0088] The present invention and its embodiments have been described above. This description is not restrictive. The accompanying drawings are only one embodiment of the present invention. The actual structure is not limited to this. In short, if a person skilled in the art is inspired by this description and designs a similar structure and embodiment without departing from the spirit of the present invention, such design should fall within the protection scope of the present invention.

Claims

1. A method for preventing derailment, based on an anti-derailment device, said device comprising a central control unit and an edge computing unit, characterized in that: Including the following steps: S10: The edge computing unit acquires data collected by the level and speed sensors and transmits it to the central control unit as vehicle monitoring data. The central control unit acquires track monitoring data in real time based on a differentiated acquisition strategy. S20: The central control unit integrates on-board monitoring data and track monitoring data, compares them with the preset four-level derailment risk level, and sends the generated risk level information to the edge computing unit; S30: After issuing risk level information, the central control unit relies on the preset intelligent matching algorithm to synchronously and collaboratively control the servo motor and hydraulic device to complete parameter adaptation and safety monitoring before intervention. S40: The edge computing unit adjusts the bogie's center of gravity by controlling the adapted servo motor to adjust the counterweights based on the risk level information, and adjusts the damper state by controlling the hydraulic device. Finally, it evaluates the intervention effect and makes dynamic adjustments through dual-end monitoring.

2. The method for preventing derailment according to claim 1, characterized in that: Step S10 includes the following steps: S101: The edge computing unit acquires the train's horizontal status and speed parameters collected by the level gauge and speed sensor according to the corresponding cycle, and obtains the raw monitoring data; S102: The edge computing unit filters, reduces noise, and standardizes the collected raw detection data before generating vehicle monitoring data and transmitting it to the central control unit. S103: The central control unit, based on a differentiated acquisition strategy, synchronously acquires track monitoring data collected by the track-side monitoring module according to the corresponding cycle.

3. The method for preventing derailment according to claim 1, characterized in that: Step S20 includes the following steps: S201: The central control unit receives the vehicle monitoring data transmitted by the edge computing unit and simultaneously collects the track monitoring data; S202: The central control unit integrates and extracts features from the on-board monitoring data and track monitoring data, generates multimodal correlation information, and classifies the current operating status into risks based on preset risk assessment rules to obtain derailment risk level information; S203: The central control unit sends the divided derailment risk level information to the edge computing unit; S204: The edge computing unit receives risk level information and calls the preset risk level response strategy.

4. The method for preventing derailment according to claim 3, characterized in that: In step S204, the derailment risk level includes four levels: no risk, low risk, medium risk, and high risk. The corresponding strategies for each risk level are as follows: When there is no risk: the edge computing unit controls each monitoring device to maintain routine data acquisition and inspection, while the central control unit only monitors the basic parameters of the motor and hydraulic system; When the risk is low, the edge computing unit pushes warning prompts to the driver through the vehicle terminal and provides voice reminders to pay attention to key indicators; In cases of moderate risk, the edge computing unit triggers an active intervention command to control the servo motor and hydraulic system to correct the lateral movement of the wheelsets and the tilting posture of the bogie, and simultaneously sends a deceleration suggestion to the driver; In cases of high risk, the edge computing unit works in conjunction with the train braking coordination unit to perform graded braking, while simultaneously sending a signal to the trackside control system to put the passive protection module into standby mode.

5. The method for preventing derailment according to claim 1, characterized in that: Step S30 includes the following steps: S301: After issuing risk level information, the central control unit establishes a dynamic correlation model between motor output torque and hydraulic circuit pressure based on a preset intelligent matching algorithm. S302: The central control unit uses a dynamic correlation model to precisely match the power output of the servo motor and the oil pressure and flow of the hydraulic device, ensuring that the two actions respond synchronously to the risk level requirements. S303: Based on redundant sensor monitoring groups, the servo motor speed and hydraulic device oil temperature are monitored and verified in real time through dual channels.

6. The method for preventing derailment according to claim 1, characterized in that: Step S40 includes the following steps: S401: The edge computing unit, based on the adapted servo motor and hydraulic device, controls the servo motor to adjust the counterweight according to the risk level information, thereby changing the bogie counterweight distribution to adjust the center of gravity. S402: The edge computing unit synchronously controls the hydraulic device to drive the damper, thereby adjusting the damping coefficient and the extension stroke; S403: The on-board and trackside monitoring modules synchronously acquire optimized operation data after intervention and transmit it to the edge computing unit; S404: The edge computing unit performs feature comparison and trend analysis on the intervention effect based on optimized operation data, and feeds back the generated analysis results to the central control unit; S405: If the risk level is reduced to no risk or low risk, the active intervention shall be gradually lifted in stages according to the preset sequence. If the risk is not reduced or escalated, an enhanced intervention command will be triggered to continuously adjust the adjustment range of the counterweight and the damping state of the damper until the risk is controllable.

7. An anti-derailment device, applied to the anti-derailment method according to any one of claims 1-6, characterized in that: The device includes an integrated box (1), a counterweight assembly (2), and a moving assembly (3). An edge computing unit (101) is installed inside the integrated box (1). The counterweight assembly (2) is integrated inside the integrated box (1). The integrated box (1) is fixedly installed above the moving assembly (3) based on a top suspension member (102). A hydraulic device (301) and a damper (303) are installed on the moving assembly (3). The hydraulic device (301) is used to adjust the damping coefficient of the damper (303).

8. The anti-derailment device according to claim 7, characterized in that: The integrated box (1) is symmetrically equipped with two counterweight components (2). Each counterweight component (2) includes a servo motor (201), a counterweight rope (202), a fixed pulley (203), and a counterweight (204). The servo motor (201) is fixedly installed inside the integrated box (1). The servo motor (201) is fixedly connected to the counterweight (204) after passing over the fixed pulley (203) based on the counterweight rope (202). The counterweight (204) is divided into multiple parts connected in series on the counterweight rope (202).

9. The anti-derailment device according to claim 7, characterized in that: The moving component (3) includes two traveling wheels (304) connected by a connecting shaft (305). Each traveling wheel (304) is provided with a limiting component (306) on both sides to prevent derailment. Each limiting component (306) is also fixedly mounted with a corresponding hydraulic device (301) on its top. The hydraulic rods (302) of the hydraulic devices (301) on both sides are fixedly connected to dampers (303).

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