2338results about "Railway traffic control systems" patented technology

The invention relates to the technical field of high-speed rail platform safety monitoring, and discloses a high-speed rail platform area intrusion detection and early warning alarm system, which comprises an acoustic and vibration sensor network deployed in a platform area and used for collecting environment signals in real time, the edge calculation unit extracts signal features and compares the signal features with a dynamically maintained environmental rhythm feature baseline to generate a detuning event mark, and the detuning mode analysis device identifies an abnormal mode through space-time correlation and triggers an alarm. According to the method, early perception of subtle anomalies is realized by constructing a multi-modal environment rhythm baseline, active perturbation injection and differential response analysis technologies are combined, the recognition capability of a silent target is remarkably improved, meanwhile, the monitoring continuity under an extreme working condition is ensured by using an elastic baseline adaptive mechanism, and the detection accuracy is improved. And a closed-loop security and protection system from passive sensing to active discrimination is formed.

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.

The invention relates to the technical field of subway information broadcast control, and discloses a subway information broadcast control method based on time period scheduling. The method comprises the steps of collecting multi-source monitoring data of a subway operation environment in real time, wherein the multi-source monitoring data comprises passenger flow data, train arrival data and emergency event report data; dividing the current operation cycle into a plurality of continuous time slices based on a preset time period division rule, and generating a corresponding time period identification code for each time slice; matching a target broadcast control template from a broadcast control strategy library according to the time period identification code, and performing parameter dynamic filling on the target broadcast control template in combination with the multi-source monitoring data; and performing logic verification on the target broadcast control template after parameter filling, triggering a broadcast control decision reconstruction process when verification is abnormal, and generating an executable broadcast control instruction set when verification is normal. According to the method, operation requirements of different time periods are dynamically adapted, so that the accuracy and timeliness of subway information broadcast control are improved, and the passenger travel experience and the operation efficiency are optimized.

The embodiment of the invention provides an urban rail signal system fault diagnosis method based on a knowledge graph and a large model, and the method comprises the steps: collecting system operation logs, state parameters and fault information in real time, and carrying out the data preprocessing and standardization; based on historical fault data, a fault classification and prediction model is constructed through feature extraction and mode recognition, and automatic fault recognition and risk early warning are achieved; constructing a fault diagnosis knowledge graph, and establishing an association relationship among entities such as equipment, faults, reasons, maintenance schemes and the like; a pre-training large language model and a LoRA technology are adopted for efficient fine tuning, a fault diagnosis reasoning model is trained, and end-to-end generation from fault description to diagnosis and maintenance suggestions is achieved; the knowledge graph and large model output are fused, real-time and historical data are combined, multi-path fault analysis and comprehensive diagnosis are carried out, and a diagnosis report is generated and displayed. The intelligent level, accuracy and efficiency of fault diagnosis can be improved, and technical support is provided for intelligent operation and maintenance management.

The invention discloses an interval occupation logic checking method, a train control system, a storage medium and electronic equipment, which are used for automatically blocking a standard railway line, and the method comprises the following steps: acquiring train position information and a train type; acquiring track circuit data, and judging a track section state; and generating a corresponding signal permission for the train based on the train position information, the train type and the track section state, and judging the logic state of the corresponding block partition based on the signal permission. The method has the advantages that the normal train, the fault train and the non-moving block train can be ensured to safely run on the automatic block system railway line at the same time, the normal train can still adopt the moving block system and does not need to be degraded into the automatic block system, the running density of the normal train is improved, and the running efficiency is improved. Therefore, the traffic capacity of the automatic block type railway line is improved.

The invention discloses a rail transit dispatching cooperation system and a rail transit dispatching system, and relates to the technical field of rail transit, the rail transit dispatching cooperation system comprises a time phase observation module, a time sequence analysis module, a conflict prediction module, an alignment correction module, a state determination module and a closed-loop extinguishing module, and fusing the time service link with the time mark data of the train control system to generate a continuous time sequence fingerprint baseline for identifying a scheduling switching boundary. According to the method, frequency mutation characteristics are extracted by constructing a time sequence fingerprint baseline, scheduling dislocation risks are identified, phase correction budget is generated, cross-interval scheduling alignment is achieved through double mirror image anchor points, judgment accuracy is guaranteed by combining buffer cone delay signal collection and double-channel verification, and finally, conflicts are absorbed through inverse phase traction and shadow periods, so that scheduling accuracy is improved. And scheduling rhythm closed-loop extinguishing control is realized.

The invention relates to the technical field of artificial intelligence and computer vision, discloses a subway key component fault detection method and system based on an AI visual large model, and aims to solve the problems of low detection precision, weak generalization ability, insufficient multi-mode understanding, poor real-time performance and lack of state evolution modeling in the prior art. The method comprises the following steps: acquiring images of key components through a multi-view industrial camera array, and performing distortion correction, illumination normalization and noise suppression; a pre-trained visual large model is utilized to extract deep space features, and modeling is carried out on a continuous frame feature sequence through bidirectional LSTM to capture a time sequence change trend. By introducing the large-scale visual large model and spatio-temporal joint modeling, the identification capability of tiny defects is improved, the discrimination stability is enhanced, high-precision and low-delay automatic detection is realized, the false alarm rate and the omission ratio are remarkably reduced, and the detection efficiency and the system maintainability are improved.

The invention relates to the technical field of intelligent traffic, in particular to a subway traffic operation decision adjustment system and method based on a large visual screen, and the system comprises a perception data module, a data processing center, a large visual screen interaction platform, an intelligent instruction decision engine, and a dynamic adjustment unit. Wherein the sensing data module collects train positioning data, platform monitoring video streams, gate passing data and environment sensor data in real time; integrating and analyzing the data by the data processing center, and mining potential modes, association relationships and abnormal conditions in the data; the visual large-screen interaction platform presents a line network congestion thermodynamic diagram, equipment fault positioning and passenger flow prediction trend in real time; the intelligent instruction decision engine is used for dynamically generating a train shift adjustment strategy and an emergency dispersion scheme; and the dynamic adjusting unit dynamically adjusts the electronic guide screen and the platform broadcast, and dynamically dispatches the train. Therefore, the problems of lagging abnormal response, unreasonable resource allocation, low efficiency and the like in the prior art are solved.

The invention provides a train operation control method and device under severe weather, and the method comprises the steps: obtaining train idling slip information sent by a train automatic protection subsystem or a train control and management system, and determining a rail slippery state according to the train idling slip information; determining a severe weather mode instruction of the target train based on the rail slippery state and the weather state; and sending a severe weather mode instruction to the train automatic protection subsystem or the train control and management system, wherein the severe weather mode instruction is used for indicating a target train in the target operation area to enter a severe weather mode. According to the train operation control method and device in the severe weather, the severe weather mode instruction of the target interval is determined according to the wet and slippery state of the rail and the weather state, safety protection can be carried out on the guaranteed emergency braking rate in the severe weather, and the situation that due to the fact that the train braking adhesion coefficient is reduced to break through the existing design boundary, the train operation efficiency is improved is avoided. Therefore, the safety of train operation is improved.

The invention discloses a safety detection system for a high-speed rail transit corollary equipment structure. The safety detection system comprises an excitation response module, an infrared heat source image acquisition module, a parameter monitoring module, an image preprocessing module, a heat source feature extraction module and a structure anomaly recognition module. In the train operation process, the system excites trackside equipment structure response through train body aerodynamic disturbance, thermal response images are collected through high-frame-rate infrared imaging, and image standardization processing is carried out based on disturbance intensity and the relative distance. And the system further extracts thermal response characteristics of the equipment structure area, and compares the thermal response characteristics with a normal template to realize abnormal structure identification and positioning. Under the condition that train operation is not affected, non-contact, high-precision and intelligent detection of the structure state of the trackside equipment is achieved, and the method has the advantages of being flexible in deployment, accurate in recognition, high in real-time performance and the like and is suitable for rail transit operation and maintenance scenes.

The invention relates to the technical field of image recognition and understanding, and discloses a high-speed rail platform intrusion early warning system based on image processing, which comprises a main analysis unit, an interference source sentry unit and a collaborative decision controller, and the collaborative decision controller not only dynamically adjusts a time sequence association window according to the apparent velocity estimated by the interference source sentry unit, but also performs self-diagnosis on the health state of the interference source sentry unit by monitoring long-time-history statistical correlation. The technical bottleneck of mutual restriction of sensitivity and anti-interference performance in traditional statistical flow analysis is solved, so that high detection capability and extremely low false alarm rate of a weak shielding target can be kept under the working conditions of complex interference and sensor failure.

The invention provides a train integrity detection method and system for constructing a dynamic envelope based on a multi-mass-point model, and belongs to the technical field of rail transit train operation safety detection. Estimating the real-time length of the baseline by using Kalman filtering; pID control is adopted to analyze and calculate the telescopic displacement of the carriages in the train running process; and comparing the calculated baseline length with the train safety envelope, and judging whether the integrity state of the train is normal or not according to a comparison result. According to the invention, the train length is detected by using the double-difference carrier phase; a train dynamic safety envelope is constructed, a train multi-mass-point model is constructed by researching longitudinal stress analysis such as resistance and workshop acting force of a high-speed train, and compartment extrusion displacement in the train running process is analyzed and calculated through PID control. A train dynamic safety envelope is formed by the data, communication delay and a redundancy threshold value and serves as a judgment basis of train integrity detection, and the efficiency and the real-time performance of train integrity detection are improved.

The invention discloses a rail transit anomaly detection method and device based on a digital twin technology, and relates to the field of artificial intelligence, the field of big data or other related fields, and the detection method comprises the steps: collecting environment perception data and video monitoring data of at least one target road section, and obtaining a real-time data stream in a first target time period; analyzing the real-time data flow based on a preset abnormal behavior rule to obtain an abnormal analysis result; a digital twinborn model is called, the digital twinborn model is detected according to the abnormal analysis result and the real-time data flow, a detection result is obtained, and the digital twinborn model is used for synchronously reflecting the actual physical environment, the basic equipment layout and the equipment operation state in the rail transit scene; and generating an anomaly detection report based on the detection result and triggering an anomaly warning. The technical problem that the emergency response speed is low due to the fact that a traditional video monitoring system lacks intelligent means in on-orbit traffic elevated section safety supervision in the prior art is solved.

The invention discloses a train driving control method and related equipment, and relates to the technical field of rail transit, the method comprises the steps that multi-source sensing data of a target train in a running state is acquired, and the multi-source sensing data comprises a speed characteristic parameter, a space positioning parameter and an environment disturbance parameter; performing dynamic feature extraction on the multi-source sensing data to obtain time-space correlation feature parameters; inputting the time-space correlation characteristic parameters into a preset data fusion model, and performing dynamic compensation through adaptive weight adjustment to obtain accurate train speed information and accurate position information; and performing driving control on the target train according to the accurate train speed information and the accurate position information. According to the invention, through multi-source information fusion and high-precision speed positioning extraction, the sensing accuracy and active adjustment capability of the train control system can be improved.

The invention provides a multi-system fusion train control method and device, and relates to the technical field of rail transit, and the method comprises the steps: deploying an area controller at a preset train station; acquiring the current driving position of the train based on the area controller; based on the current driving position, a communication control instruction between a train-mounted automatic train protection system of the train and an automatic train monitoring system of the train station is determined; and performing communication control between the train automatic protection system and the train automatic monitoring system based on the communication control instruction. According to the multi-system fusion train control method provided by the invention, the rail systems to which different positions belong are adapted through the dynamically adapted communication control instruction, communication interruption caused by protocol differences under different rail systems is eliminated, seamless communication between different system devices in a rail transit multi-system fusion system is ensured, and the reliability of the rail transit multi-system fusion system is improved. And high-efficiency and low-cost multi-system fusion train control is realized.

The invention discloses a train protection zone processing method based on a train-to-train communication architecture, which comprises the following steps that: an ATP (Automatic Train Protection) of a fault train submits an application for requesting to establish a protection zone to an RC (Remote Control), and the RC sends inquiry information to all trains which establish communication with the RC in a control zone of the RC; after receiving inquiry information of the RC, the trains check the relation between the trains and the protection area and reply, and if all the trains reply to agree to establish the protection area, the RC establishes the protection area; according to the distance between the train inside and outside the protection area and the fault train and the corresponding driving direction, the running state of the train is determined; the running state is emergency braking or continuous running; and after the fault train does not report derailment to the RC or an obstacle exists on the track, the protection area of the fault train is cancelled. The safety and efficiency of train operation are improved.

The invention provides a rail transit remote monitoring method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the fault causal reasoning and fault propagation simulation of an equipment fault event based on artificial intelligence when an equipment abnormal event occurs in a rail transit scene through remote monitoring; and performing multi-modal early warning based on a fault causal reasoning result and a fault propagation simulation result. According to the rail transit remote monitoring method and system based on artificial intelligence, fault causal reasoning and fault propagation simulation are carried out on the equipment fault event based on artificial intelligence, multi-modal early warning is carried out based on the fault causal reasoning result and the fault propagation simulation result, and the reliability of the system is improved. The system has sufficient monitoring efficiency to a great extent when facing sudden faults, complex fault modes and large-scale data analysis in a rail transit scene, and monitoring accuracy and response timeliness are improved.

The present disclosure is applicable to the field of railway signal control, and provides a throat turnout group determination method, comprising: constructing a route direct conflict turnout dictionary and a throat-area turnout group dictionary on the basis of station turnout information and route information; constructing a route throat-area direct conflict turnout group dictionary on the basis of the route direct conflict turnout dictionary and the throat-area turnout group dictionary; constructing a set of occupied throat turnout groups on the basis of the throat-area turnout group dictionary and the route throat-area direct conflict turnout group dictionary and in combination with the direction of a route and a reception / departure type; and determining a turnout group having the longest total occupation time in the set of occupied throat turnout groups as a target throat turnout group. The present disclosure can enhance the computational efficiency of station throat operational capacity and solve the problem of being prone to errors caused by manual analysis.

The invention discloses a train fault state detection method and system based on artificial intelligence, and relates to the technical field of train fault state detection. The method comprises the steps that multiple types of sensors are arranged at key parts of a train, state data such as temperature, vibration, electricity, energy consumption and noise are collected in real time, local receiving, preprocessing and wireless uploading of the data are achieved by means of a mobile terminal, and a cloud platform conducts multi-dimensional analysis and fault recognition through an artificial intelligence algorithm on the basis of a health assessment model. According to the train fault diagnosis system and method, health indexes and early warning information are generated and pushed to operation and maintenance personnel in real time, the system supports overhaul process recording and multimedia information uploading, information archiving and analysis tracing are achieved, the accuracy and response efficiency of train fault diagnosis are remarkably improved, the operation and maintenance cost is reduced, and the safety and intelligent level of a railway system are enhanced.

The invention discloses a train platform tracking processing method and system based on a train-to-train communication architecture, and the method comprises the steps: transmitting a retreating request message to a rear train when the position of the current train partially coincides with a platform and has a retreating intention; when the rear vehicle receives the retreating request message sent by the front vehicle, judging whether a preset condition is met or not, and if the preset condition is met, allowing the front vehicle to retreat and sending a retreating allowing message to the front vehicle; if the front train receives a retreating permission message sent by the rear train, train traction is not cut off, train retreating is permitted, and a retreating request message continues to be sent to the rear train till the front train finishes retreating. The train tracking efficiency is improved.

The invention discloses a heavy haul train automatic driving curve planning method, electronic equipment and a storage medium. The method comprises the steps that a DP state transition table is loaded, and a plurality of initial states, a plurality of actions capable of being adopted in each initial state and a transition state capable of being reached by each action are defined in the DP state transition table; acquiring a protection curve as a speed limit line, and drawing according to the protection curve to obtain a guide line; performing curve planning by taking N DP step lengths as a cycle, for each DP step length, sequentially traversing each migration state corresponding to the initial state of the DP step length from top to bottom in the DP state migration table, and performing judgment based on a speed limit line and a guide line to obtain respective target migration states of the N DP step lengths; and generating a speed-mileage planning curve of the train according to the final speed of a differential interval obtained by performing dynamic differential calculation by adopting the action corresponding to the target migration state of each DP step length. According to the invention, the planning success rate and fault tolerance can be improved.

The invention provides the unsupervised learning-based fault diagnosis method and system for detecting wheel out of round, which belongs to the technical field of machine learning fault diagnosis. Characteristic signals of train wheels will be acquired. The pre-trained detection model is adopted to process the characteristic signals of the train wheels to be detected, so as to obtain the wheel roundness state results. As for the collected characteristic signals, the invention constructs a subway wheel out of round detection method based on unsupervised learning for collected characteristic signals, which are deployed to computer equipment capable of executing computer programs, inputting characteristic signal data collected by a subway wheel out of round monitoring device based on rail wayside response into the computer equipment to obtain the wheel roundness state.

The present invention relates to the technical field of rail transit signaling systems, and in particular to a train control system, method and apparatus for heterogeneous verification of movement authority (MA). The system comprises: a ground-based temporary speed restriction server configured to send, to an onboard device of a target train, location information of all trains within a section corresponding to the target train; a ground-based radio block center configured to: calculate MA on the basis of the location information of the target train and location information of a train preceding the target train; and send the MA and identification information of the preceding train to the onboard device of the target train; and the onboard device configured to verify and correct the MA on the basis of the identification information of the preceding train and the location information of all the trains. In the present application, a heterogeneous MA calculation and verification mechanism is adopted, thereby reducing the risk of errors due to MA calculation by a single device.

A train operation intelligent dispatching system and method are provided, where the system includes: a data acquisition and control module, configured to collect multi-source data affecting train operation; a data processing module, configured to perform data aggregation on the multi-source data, and process the multi-source data to form multi-source data in a unified data format; a multi-disciplinary data resource pool, configured to perform real-time storage and updating of the multi-source data in the unified data format, and store historical multi-source data; an intelligent fault analysis module, having intelligent fault analysis models therein, configured to perform fault analysis based on the multi-source data to obtain fault analysis results of corresponding disciplinary systems, and output fault advance warnings of corresponding disciplinary systems according to the fault analysis results; and a process preplan module, configured to provide preplan handling processes corresponding one-to-one with external multi-disciplinary systems.

The invention discloses a signal control system for a mining locomotive, and aims to solve the problems of weak interference resistance and low safety of a traditional system. The system comprises a signal acquisition module, a dynamic frequency coding processing module, an intelligent decision-making module, an execution module, a communication module and a power supply module. The signal acquisition module acquires the position, speed and environmental parameters of the locomotive through an infrared position, speed and temperature and humidity sensor; the dynamic frequency coding module monitors the signal-to-noise ratio of a sub-band every 10 ms, when the signal-to-noise ratio of the sub-band is lower than 15 dB, the sub-band is automatically switched to a high-signal-to-noise-ratio sub-band larger than or equal to 20 dB, an encryption mapping table is generated for synchronous updating, and the equipment deals with sudden interference through an emergency band. The intelligent decision-making module generates a control instruction, and speed adjustment and parking are achieved through the execution module. An explosion-proof cable and a low-frequency through-the-earth technology are combined for communication, and a power supply is of an explosion-proof type and has multiple protections. The system improves the anti-interference performance and safety of signal transmission, adapts to the mine environment, and supports the intelligent operation of mine transportation.

A sensor device (3) for detecting strains in a linear infrastructure component (12), in particular a track rail, comprises a first sensor unit (16, 16') with a first support (28) and at least one strain sensor mounted on the first support (28) for detecting a strain at the first measuring point (19), a second sensor unit (17) with a second support (29) and at least one strain sensor mounted on the second support (29) for detecting a strain at the second measuring point (20), a coupling means (18) connected to the first support (28) and the second support (29) for defining a measuring distance (d) between the first measuring point (19) and the second measuring point (20) along a longitudinal direction (21) of the linear infrastructure component (12), a measuring arrangement (19) with the sensor device (3), a method, and an application device for applying the sensor device (3).

Methods and systems for managing operations of a classification yard. In embodiments a release speed, coupling speed, and / or a predicted speed at one or more points of a route along which a cut is being routed is determined. A set of event messages of events that occurred during the traveling of the cut is generated. Real-world measurements associated with an actual speed of the cut at the one or more points of the route are obtained. Coefficients associated with the predicted speed of the cut at the one or more points are autotuned based on the real-world measurements, a status of one or more devices used to route the cut is determined based, at least in part, on thresholding analysis applied to the real-world measurements, and the set of event messages is stored in an event log for subsequent replaying in a graphical user interface (GUI).

The invention discloses an AI-based rail transit dynamic safety early warning system, which comprises a sensing layer for deploying an intelligent sensor network with dynamically adjustable spacing, integrating a steel rail health monitoring suite to carry out microdefect detection on a steel rail, capturing vibration deformation characteristics under high-speed operation by a dynamic monitoring array, acquiring external environment data by an environment sensing module, and sending the external environment data to an early warning layer; preprocessing the collected data by utilizing an edge computing node; according to the cognitive layer, a line adaptive layer performs adaptive fusion on multi-line features through three-stage training of'basic training-meta training-fine tuning 'in combination with a dynamic weight generation mechanism, meanwhile, a causal cognitive module constructs a three-stage variable causal graph, a hybrid inference engine combines a CLIPS symbol inference engine, a Bayesian probability network and a D-S evidence theory, and the line adaptive layer performs multi-line feature fusion on the basis of the CLIPS symbol inference engine. Logic deduction and uncertainty quantification of fault attribution are realized; according to the decision-making layer, a dynamic threshold generator adjusts an early warning boundary in real time based on an LSTM prediction model, and an emergency plan engine recommends a maintenance strategy in combination with a digital twinborn simulation result.

The invention discloses a heavy-load freight direct-current electric locomotive on-board platform and a train operation curve calculation method. Step-by-step iterative optimization is carried out through a dynamic programming algorithm. Presetting operation steps and step lengths, and defining a selectable action set in each step length; and with the current state of the train as a starting point, evaluating each action in the action set in each iteration step, and calculating the next train state which may be transferred to. And evaluating all possible train state changes by adopting a target cost function, sorting according to the cost values from small to large, and preferentially selecting the action with the minimum cost value for subsequent calculation. And if all the action cost values of the current step exceed the limit, backtracking to the previous iteration step for reselection. And after iteration to the maximum step number, storing all train state changes, and finally obtaining an optimal train operation curve under the constraint of the target function. The method optimizes a control strategy through a dynamic programming algorithm, improves prediction precision, optimizes action selection, accelerates convergence, reduces redundancy, and improves operation stability, safety and algorithm efficiency.

Systems and techniques for intelligent detection of abnormal conditions associated with a shipping container. A system includes an on-site system configured to capture sensor data associated with a condition of a container carried by a train car of a train, analyze the sensor data to determine whether the condition of the container indicates an abnormal condition, and identify one or more of the train car, the container, and the train. The system also includes a backend system configured to receive a detection message from the on-site system and generate an alert signal in response to a determination that the condition of the container indicates an abnormal condition. The alert includes the abnormal condition and identification information, and causes one or more remedial actions to respond to the abnormal condition of the container.