3535results about "Signalling indicators on vehicle" patented technology

The invention relates to the technical field of railways, and discloses a railway passenger train operation state monitoring system based on artificial intelligence, which comprises a multi-modal sensor array, an edge AI judgment platform and a cloud intelligent decision center. According to the railway passenger train operation state monitoring method and system based on artificial intelligence, 28 parameters of a contact network, a running gear and the like are collected in real time through a multi-modal sensor array, an edge AI judgment platform utilizes a cross-modal fusion algorithm to deeply mine multi-source data potential association, the fault diagnosis accuracy is improved, and the fault diagnosis efficiency is improved. The cloud intelligent decision center dynamically aggregates gradient parameters of the edge end model based on federated learning, filters abnormal nodes and updates the abnormal nodes in an hour-level period, and constructs a digital twinborn model in combination with a Spark framework to realize dynamic parameter optimization; the fire-fighting early warning fusion model is linked with the air conditioner pressure and the compartment sealing state correction threshold value through a three-stage mechanism of parameter initial judgment, visual verification and environment verification, it is ensured that the early warning response time is shorter than 200 ms, and cooperation with the overall state of the train is achieved.

The invention discloses a railway freight train data acquisition method and system based on multi-sensor fusion, and relates to the technical field of railway transportation, and the method comprises the steps: detecting the operation state and position of a train in real time through wireless communication, and carrying out the self-inspection of each sensor when the train is detected to be about to enter a monitoring region; constructing a three-dimensional health state model of the train through three-dimensional reconstruction and synchronous positioning according to the comprehensive state data of the train; in combination with a three-dimensional health state model and a side cloud collaborative architecture, layered processing and dynamic optimization of train comprehensive state data are accelerated by using a quantum algorithm, and abnormal features are identified in real time; the abnormal features are analyzed through deep learning and a time sequence analysis algorithm, and alarm information is generated and fed back to the edge computing terminal; according to the method, the running state of the train and the cargo state data are deeply fused through the convolution operation of the three-dimensional health state model and the space-time diagram, so that the global perception capability of the data is improved.

The invention relates to the technical field of big data, and discloses an urban rail transit emergency processing method and system based on a visual large model, and the method comprises the steps: collecting visual data, sound data and equipment operation data at a platform and a carriage of urban rail transit, and carrying out the preprocessing and timestamp synchronization; performing dynamic frame difference processing on continuous video frames of the visual data to generate a two-dimensional motion heat map, and performing space-time aggregation; constructing a three-dimensional digital model based on engineering drawings of the platform and the carriage, and establishing a mapping relation between the two-dimensional motion heat map and the three-dimensional digital model; performing abnormal behavior detection on a mapping result, performing multi-modal fusion analysis in combination with sound data and equipment operation data, and determining the severity of an abnormal event; emergency response strategies are formulated according to severity levels of the abnormal events, a control instruction is sent to the rail transit equipment through an industrial protocol interface, and abnormal event information is pushed to a control center, inspection personnel and passenger terminals.

The invention relates to the technical field of electric vehicle control, and provides an intelligent new energy locomotive power distribution and energy recovery control system and method. The system comprises a multi-source information sensing layer, an intelligent decision control layer and an execution feedback layer. The multi-source information sensing layer collects the state of a vehicle and external environment data. The intelligent decision control layer generates a power distribution and energy recovery instruction through data fusion and preprocessing, fuzzy logic assistance, reinforcement learning decision and cooperative work of a multi-objective optimization module; and the execution feedback layer executes the instruction, monitors feedback in real time, and optimizes related actions. According to the method, advanced technologies such as reinforcement learning and fuzzy logic are fused, complex and changeable driving scenes are accurately dealt with, self-adaptive optimization of power distribution and energy recovery strategies is achieved, the energy recovery efficiency is improved, power distribution is accurate and efficient, dynamic adjustment can be achieved according to driving intentions and working conditions, the driving safety and comfort are guaranteed, and meanwhile the driving efficiency is improved. And efficient utilization of energy is realized.

A system and method generate a trip plan for a trip of a vehicle system along a route. The usage of an engine during the trip is determined based on engine operational parameters, energy storage device operational parameters, and one or more objectives of the trip desired to be achieved. The usage of the energy storage device during the trip is also determined based on the engine operational parameters, the energy storage device operational parameters, and the one or more objective, including when to charge or discharge the energy storage device during the trip.

The invention provides a metro driver abnormal behavior recognition method based on multi-modal data fusion. The method comprises the steps that metro driver abnormal behaviors are recognized based on multi-modal data fusion, track positioning and platform screen door sensor data are fused to detect the position of a train, and a station entering confirmation instruction is generated; according to the data of the seat pressure distribution sensor, driver off-seat inspection is judged; generating an outbound completion event in combination with a track circuit signal, an ATO instruction and the like; analyzing console touch pressure, voice instructions, hand actions and the like to verify operation compliance, and triggering an alarm when the operation is abnormal; aggregating results at edge computing nodes, encrypting and transmitting the aggregated results to a central scheduling system, dynamically mapping driver behaviors in a digital twin cockpit, and automatically triggering hierarchical alarms and associating data snapshots when the driver behaviors are abnormal; according to the invention, accurate recognition and real-time early warning of subway driver behaviors can be realized by means of multi-modal data fusion and intelligent analysis, and the subway operation safety and the emergency response efficiency are greatly improved.

The invention discloses a train dispatcher behavior anomaly detection system based on LSTM-FCN and a dynamic intervention method thereof, and relates to the technical field of intelligent monitoring. Scheduling operation time sequence data, environment state data and physiological monitoring data are collected in real time, a space-time joint feature vector is constructed, and a train dispatcher behavior anomaly detection result is obtained. The LSTM-FCN hybrid network is used to extract time sequence dependence features and spatial pattern features, and an attention weight matrix generated by physiological data and a compensation factor matrix generated by environmental parameters are combined to dynamically calculate a comprehensive abnormal probability value; and when the probability value exceeds a self-adaptive adjustment threshold value, triggering a hierarchical intervention mechanism based on the driving scheduling knowledge graph to realize progressive intervention from interface prompting to manual takeover. By fusing multi-modal data and self-adaptive dynamic compensation, the problem of poor adaptability to complex scenes due to adoption of a static model in traditional train monitoring is solved, and the accuracy and intervention timeliness of abnormal behavior detection of the train dispatcher are remarkably improved.

The invention discloses a train control method and a train control system based on credible interval entry check. The train control method comprises the following steps: starting a backup command; the temporary speed limit server starts a sending module used for sending authorization to a train self-protection system; performing interval credible entry check; determining the existence condition of the train in the interval; the temporary speed limit server updates a train existence condition list in the interval; the train obtains a front driving permission; the train runs according to the running permission. According to the train control method and the train control system based on the credible interval entry check, the axle counting equipment is arranged at the interval entrance, software of the temporary speed limit server only needs to adjust individual modules, and the software of the temporary speed limit server can be only used for recording the train condition in the interval and is not used for authorized calculation, so that the train control method and the train control system are convenient to use. The deployment cost of the temporary speed limit server is reduced, the transportation efficiency under the condition of a CTCS-2 system fault is improved, and the toughness of the CTCS-2 system is improved.

According to the novel transponder and the Beidou short message-combined realization function and application method and system, multiple functions are realized by utilizing multiple combinations of ground and vehicle-mounted transponder system equipment, the novel transponder can be applied to multiple scenes, the equipment types can be simplified, the construction cost can be reduced, and the maintenance workload can be reduced; beidou positioning and short message functions, positioning and communication of wireless communication and the like are used as supplements to perfect train operation control and other functions, and the transportation efficiency and safety are improved.

A rail train and an operation planning method and apparatus therefor, a device, and a storage medium, relating to the technical field of intelligent driving. The method comprises: acquiring planning information of a train formation; acquiring following situation information of a current train in the train formation; and on the basis of the following situation information and the planning information, using a speed planning model to acquire a local operation curve of the current train, wherein the speed planning model comprises a longitudinal dynamics model, a constraint condition, and an objective function. In the present invention, an operation state of each following train in the train formation can be planned and generated by using the constructed longitudinal dynamics model of the rail train and the collaboratively planned objective function and constraint condition, so that distributed planning and control of the train formation are realized, the calculation load of a single train can be effectively reduced, and the requirements for real-time performance and safety of communication between trains can also be reduced, thereby reducing the cost of the rail train.

The invention discloses an electric locomotive rail obstacle identification method, device and system and electronic equipment, and relates to the technical field of rail transit. The method comprises the following steps: acquiring geographic information along a track and current positioning information, acquiring current radar information to perform obstacle detection when a driving state is determined according to the current positioning information, and performing a first alarm and acquiring current video image information when a suspected obstacle is detected; performing time-space synchronization and data fusion on the current positioning information, the current radar information and the current video image information, and inputting the fused data, the locomotive running state data and the geographic information into a pre-established obstacle recognition model to recognize a suspected obstacle to obtain a recognition result; and determining a risk level according to the identification result, so that the electric locomotive gives a second alarm according to the risk level and takes countermeasures. According to the invention, multi-source data is acquired through various sensors, accurate identification of small targets is realized, and the safety of railway transportation is guaranteed.

The invention discloses a traction energy-saving method and system based on dynamic load flow calculation for rail transit, electronic equipment and a readable storage medium, and the traction energy-saving method comprises the steps: planning a multi-vehicle collaborative energy-saving module through an ATO single-vehicle energy-saving + ATS working diagram, a dynamic diagram adjustment module according to passenger flow requirements, a regenerative braking energy feedback module and other modules; multi-dimensional coupling conditions of power supply, vehicles, signals, tracks and the like are dynamically analyzed, dynamic load flow calculation is performed from the perspective of energy flow through a dynamic load flow calculation and analysis module of the traction power supply system, technical means such as ATO energy saving, ATS energy saving and regenerative braking energy recovery device energy saving are dynamically coordinated, unified management and cooperative linkage are performed, and the dynamic load flow calculation and analysis module of the traction power supply system is realized. Energy consumption monitoring and statistical analysis are carried out for different traction energy-saving measures, and long-term energy-saving operation effect tracking and evaluation are carried out; and an energy-saving control strategy is continuously adjusted and optimized according to an analysis result through a prediction model between line energy consumption and operation data variables, so that a better energy-saving effect in a real sense is achieved.

The invention provides a train section protection method and system capable of autonomously sensing a backup operation level, and the method comprises the steps: receiving danger source information and signal machine state information transmitted by ground equipment under the condition that the operation level of a train is an ABL level; calculating a first perception MA of the train according to the signal machine state information and the ABL level generation factor; according to the type of the signal machine corresponding to the open near road of the train and the first sensing MA, sensing MA fusion of different train routes is carried out, and a second sensing MA is obtained; extending the second perception MA according to different accurate parking scenes to obtain a third perception MA; updating the third sensing MA according to the validity of the hazard source information to obtain a fourth sensing MA; and controlling the train to perform target obstacle protection in the operation interval according to the fourth sensing MA. According to the method, automation, intelligence and reliability of a train signal system are improved, and then the efficiency and safety of interval protection of the train are improved.

The invention relates to the field of rail transit equipment, and discloses a rail transit equipment multi-source sensing data real-time fault-tolerant decision-making system, which comprises a multi-source sensing module used for collecting rail environment and locomotive state data through a 3D laser radar, a binocular camera and a Beidou positioning terminal, including obstacle, turnout, signal lamp and locomotive position information; the data fusion processing module is used for carrying out preprocessing, redundancy check and feature extraction on the multi-source sensing data to generate a fusion sensing result; and the fault-tolerant decision module is used for judging the safety state of the track based on the fusion sensing result, triggering an alarm / braking instruction and executing self-checking logic when the sensor is abnormal. Through the combination of double groups of redundant sensors and a three-level progressive fault-tolerant strategy, closed-loop control from data acquisition to safety decision is formed, the system robustness under complex working conditions is remarkably improved, and an omnibearing safety protection barrier is constructed for rail transit equipment.

Disclosed is an adaptive control method and system for train operating condition identification. The method includes acquiring train operating state data under various traction conditions and calculating traction and braking performance data. An adhesion condition characteristic data set is formed, and train adhesion conditions are divided into Nz grades based on this data set, where Nz is a natural number. The current adhesion condition grade Nd is identified using the number of adhesion condition grades and current operating state data, where Nd≤Nz, establishing a mapping relationship between an adhesion coefficient and maximum deceleration for braking under the identified grade. An optimal train protection curve is generated. By clustering and grading adhesion conditions through a clustering algorithm, the method achieves more accurate adhesion condition analysis. Adaptively generating optimal train protection curves based on adhesion condition grades enhances the reliability and safety of train operations.

The invention discloses a multi-dimensional train derailment monitoring method based on vision and vibration, and belongs to the field of rail transit, the method comprises the following steps: respectively collecting a wheel-rail contact area image and vibration data of each wheel in different directions, and carrying out space-time alignment on the wheel-rail contact area image and the vibration data; combining an edge detection algorithm and a Hough transform technology to extract visual features from the wheel-rail contact area image, extracting vibration features from the vibration data, and associating the visual features with the vibration features to generate a wheel flange transverse position-vibration feature mapping table; and establishing a D-S evidence theory fusion model based on the wheel flange transverse position-vibration feature mapping table, fusing the visual features and the vibration features by using the D-S evidence theory fusion model, and judging the train derailment risk according to a feature fusion result. According to the invention, deep coupling analysis of visual images and vibration data is realized, and the defects that the prior art cannot adapt to working condition changes, false alarms are easily generated and operation is affected are overcome.

The invention provides a driving control method, device and equipment in severe weather and a storage medium, and the method comprises the steps: calling traction brake level critical point data and running speed critical point data of a target train based on the current severe weather type; and based on the traction braking level critical point data and the running speed critical point data, the traction braking level and the speed limit value of the target train are updated respectively. According to the running control method, device and equipment in the severe weather and the storage medium, the train can automatically adapt to the severe weather for targeted adjustment, so that the probability that the train idles and slips in the severe weather is reduced, dangerous point protection failure caused by unreasonable speed limit value setting is avoided, and the safety of the train is improved. And the operation efficiency of the line can be furthest improved.

The invention provides an integrated vehicle-mounted system compatible with CTCS (China Train Control System) and CBTC (Communication Based Train Control). Comprising an integrated vehicle-mounted main control unit which is used for realizing a train control function of a CTCS system and a CBTC system, and controlling a CTCS vehicle-mounted module and a CBTC vehicle-mounted module to perform vehicle control right switching when a train crosses jurisdictions of different systems; the man-machine interaction unit is used for displaying a man-machine interaction interface in a system corresponding to the current train control mode according to the current train control mode; the sensor unit is used for collecting operation data of a train in real time and sending the operation data to the integrated vehicle-mounted main control unit; and the vehicle-mounted interface unit is used for realizing electrical connection between the CTCS vehicle-mounted module and the train and between the CBTC vehicle-mounted module and the train, and the vehicle-mounted interface unit is adaptive to the CTCS system interface and the CBTC system interface and supports a common interface mode and an independent interface mode. According to the invention, integrated design is realized, compatibility of CTCS and CBTC systems is realized, and the rapid switching capability and compatibility of train systems are improved.

The invention provides a backup degradation train control system based on rail transit intelligent perception, the system comprises existing vehicle-mounted signal subsystems loaded at two ends of a train, a vehicle interface, a bridge and an intelligent perception subsystem, the intelligent perception subsystem comprises an ATO, an ATP, an ITE, a perception device and a speed measurement device; the sensing equipment is connected with the existing vehicle-mounted signal subsystem; the switching equipment is used for switching to the intelligent sensing subsystem to run in an autonomous sensing mode when the train with the CBTC is degraded due to a fault, and the existing vehicle-mounted signal subsystem is still maintained in an RM mode; when the train which autonomously perceives running runs to the area with the upgraded CBTC, the vehicle-mounted equipment is switched back to recover running of the train CBTC; the wireless communication device is used for being in wireless connection with the vehicle-mounted signal subsystem and the trackside device. The intelligent sensing subsystem operates when the CBTC breaks down and degrades, toughness is improved, and it is achieved that the train does not get off line in the peak period.

The invention discloses a shunting automatic driving and protection technology in a full operation scene. In order to improve the safety and efficiency of shunting operation, the shunting operation system is composed of a shunting protection and auxiliary driving platform, a vehicle-mounted intelligent sensing platform, an intelligent management and control data platform and a communication subsystem. The shunting protection and auxiliary driving subsystem comprises a vehicle-mounted subsystem and a ground subsystem, the vehicle-mounted subsystem is provided with a shunting auxiliary driving vehicle-mounted host and the like, and the ground subsystem comprises a host unit and the like. The vehicle-mounted intelligent sensing subsystem can detect obstacles and give an alarm. The intelligent management and control data platform is divided into four layers including a data layer and the like. And the communication subsystem realizes communication of each module. The shunting auxiliary driving vehicle-mounted host is provided with a host and an expansion unit which are consistent in structure, the host and the expansion unit comprise a main controller and the like, two links are established between the units through communication board cards, and the controller of one system can use adjacent communication board cards. The system is used for intelligent management of railway traffic, and has the advantages of safety, high efficiency, full-scene applicability and the like.

Provided are a system and method for diagnosing operational safety of railcars in which one or more vibration sensors installed in each car of a train measure and analyze vibrations generated from the running car, running information including the travel location and travel speed of the car is added to vibration data and transmitted to a central control system, integrated running information is analyzed through pretrained artificial intelligence (AI) to estimate an abnormal part of the cars or railroad, and the AI is retrained through big data analysis.

Disclosed in the present invention are a backup system, and a train control system and an application method thereof. The backup system comprises: a lineside electronic unit, which communicates with a TIS or a station computer-based interlocking device to obtain a signal state and turnout position information; and an active balise connected to the lineside electronic unit and an onboard device, respectively; wherein the lineside electronic unit determines sent movement authority information and line data information on the basis of the obtained signal state and turnout position information; when a train passes through the position where the active balise is located, the active balise sends the obtained movement authority information and line data information to the onboard device; and when entering an enhanced backup mode, the onboard device in the train control system calculates a speed-distance control curve on the basis of the movement authority information and the line data information obtained from the active balise, so as to perform train operation supervision and protection. According to the prevent invention, when train-ground wireless communication is interrupted and a train control system is degraded to a backup mode, a train is allowed to enter a station at a higher speed.

The invention provides a train operation scheduling method based on a train-ground integrated system. The train operation scheduling method can be applied to the technical field of railway vehicle operation and management. The train operation scheduling method comprises the following steps: acquiring state monitoring information of each component configured on a plurality of candidate trains, operation mileage information of each component, maintenance record information of each component, historical operation environment information of the plurality of candidate trains and monitoring information of a plurality of to-be-operated lines; based on the state monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train, generating health state information of each candidate train; generating state information of each to-be-operated line based on the monitoring information of each to-be-operated line; and based on the health state information of each candidate train and the state information of each to-be-operated line, generating an operation scheduling plan for each candidate train so as to schedule each candidate train to operate on each to-be-operated line.

The invention discloses a train stop control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining each first deviation value of train stop in a historical time period, the first deviation value being a position deviation value between an actual stop point of a train at a platform and a preset target stop point; determining a deviation average value and a deviation standard deviation according to each first deviation value; according to the deviation average value, the deviation standard deviation and a normal distribution relational expression, a predicted deviation value of the train stopping at the next platform is determined; in the process of driving the train to the next platform, for each preset period, acquiring a first distance between the train and a target parking point of the next platform in the period; determining a second distance according to the first distance and the predicted deviation value; determining a first speed of the train in the period according to the second distance; and the train is controlled according to the first speed in the period, and the train station stopping accuracy is improved.

The invention provides an automatic mode switching method and device of an integrated vehicle-mounted system and a storage medium. The method comprises the following steps: receiving system switching information, and determining a current system and a target system according to the system switching information; according to the speed limiting information before switching and the system switching point position, the movement authorization information of the current system is used for calculating a train operation control curve, and the train speed is monitored; according to the train operation control curve and the train speed, whether the train reaches the system switching point position or not is judged in real time; when the train arrives at the system switching point position, the current system is switched to the target system, and the current system is switched to the background state; and updating the train operation control curve according to the switched speed limit information and the movement authorization information of the target system. The system can be simplified, the cost is reduced, the automatic compatible switching of the system is realized, and the system efficiency and safety are improved.

An electronic train device suitable of use on a railway vehicle includes a radio module configured, through operation of at least one processor, to support and monitor a plurality of communication channels for messages transmitted between multiple electronic train devices on multiple railway vehicles, and to repeat and / or route a transmitted message using a channel of the plurality of communication channels to provide reliable communication between the multiple electronic train devices.

The invention provides an auxiliary driving method and system for a high-speed motor train unit, a medium and equipment, and relates to the field of train operation control, and the method comprises the steps: determining an auxiliary driving working mode corresponding to an auxiliary driving request when the auxiliary driving request is detected; and calling corresponding auxiliary driving information in the auxiliary driving guidance information, the real-time auxiliary driving guidance information and the automatic driving control information according to the auxiliary driving working mode to carry out auxiliary driving. When the auxiliary driving request is detected, the corresponding auxiliary driving working mode is determined firstly, and different auxiliary driving working modes can be started in different application scenes so as to adapt to auxiliary driving of the high-speed motor train unit in different external scenes.

The invention discloses a rack rail trapped rail vehicle and a driving part and a driving assembly thereof. The rack rail trapped rail vehicle comprises a driving disc support; the driving disc assembly is installed on the driving disc support and used for being in meshing transmission with a rack on the rack rail; the driving part is connected with the driving disc assembly and used for driving the pin shaft wheel on the driving disc assembly to rotate; the wheel swing frame assemblies are arranged on the two sides of the lower portion of the driving disc support, and rolling wheels used for being matched with the special-shaped rails on the two sides of the rack rail are arranged on the wheel swing frame assemblies; the first braking device is arranged on the driving disc support and used for clamping the driving disc assembly to achieve working braking of the locomotive; the second braking device is arranged on the wheel swing frame assembly and used for clamping the special-shaped rail to achieve emergency braking of the locomotive; and the speed limiting device is mounted on the driving disc bracket, triggers the first braking device to act when the speed of the locomotive reaches a first preset speed threshold value, and triggers the second braking device to act when the speed detected by the speed limiting device is still greater than zero after the first braking device brakes.

The invention provides a train cooperative operation prediction control method and system based on a dynamic interval model, and belongs to the technical field of train operation control, and the method comprises the steps: calculating a train minimum tracking interval based on the real-time estimation state information of a train according to a train relative distance braking model; the communication delay time of the train-to-train communication system is considered, an additional safety margin is added on the basis of the minimum tracking interval of the train, and the influence of communication delay on cooperative operation control of the train is compensated; a system state space model is constructed based on the safety margin, and a train optimization control problem is formed based on the control constraint and the control target; and solving a train optimization control problem, obtaining an acceleration sequence for controlling train operation, and acting a first item of the sequence on the train to realize train operation control. According to the invention, while the tracking interval between the trains is effectively reduced, the influence of communication delay on the train operation is compensated by adding the additional safety margin, so that the train operation safety is improved, and the line transportation efficiency is improved.

The invention discloses an unmanned vehicle optimal action sequence generation system and method based on cooperation of a large model and a special model, and relates to the technical field of unmanned vehicle control. In the system, after a task understanding and decision vertical large model generates cue word segments based on instruction text information, scene state information and a task planning knowledge base, the cue word segments are divided into a plurality of cue word segments; decomposing the received task into various sub-tasks for task planning, and generating a plurality of action strategies and specific parameter calling information corresponding to the various sub-tasks, so as to obtain multiple types of action schemes; calling corresponding special model analytic operation based on specific parameter calling information of the special model of each action strategy in the current scheme, and dynamically integrating each analytic operation result to obtain an action sequence of the current scheme; and based on the action sequence of each action scheme, determining a comprehensive evaluation value of each action scheme so as to determine an optimal action sequence. The accuracy, the efficiency, the adaptability and the automation degree of generating the action sequence of the unmanned vehicle are improved.