Patent Application
20210094596
The present patent document claims the benefit of European Patent Application No. 19306236.1, filed Sep. 30, 2019, which is hereby incorporated by reference.
The present disclosure relates to rail automation, and more particularly to a system, apparatus, and method for remotely managing operation of rail vehicles.
Currently, rail vehicles have onboard control units that control the operation of the rail vehicle. Such onboard control units operate based on data received from multiple sources such as driver's cab controls, wayside units, beacons provided on the railway track, and so on. The data is further processed by the onboard control unit provided on the rail vehicle to perform one or more operations. For example, the operation may be associated with application of brakes when a speed of the rail vehicle is above a predefined speed limit. However, if an issue arises with the onboard control unit, it may not be possible to reproduce the issue at a remote development site for purposes of bug fixing. In other words, remote troubleshooting of the onboard control unit becomes difficult. Consequently, maintenance personnel may have to perform physical checks on the rail vehicle in order to resolve the issue. In one example, the rail vehicle may be taken to a maintenance workshop for resolving the issue. In another example, the maintenance personnel may visit the location of the rail vehicle for resolving the issue. Further, prevention of such issues may require rigorous testing during a development phase of the onboard control unit. Similarly, upgradation of the onboard control unit may also become difficult as it is necessary to upgrade both the hardware and the software associated with the onboard control unit. The above factors may lead to an increase in the downtime of the rail vehicle. As a result, the operation of the rail vehicle is affected.
In light of the above, there exists a need for remotely managing the operation of a rail vehicle in real-time.
Therefore, it is an object of the disclosure to provide a system, an apparatus, and a method for remotely managing operation of a rail vehicle in real-time. The scope of the present disclosure is defined solely by the appended claims and is not affected to any degree by the statements within this summary. The present embodiments may obviate one or more of the drawbacks or limitations in the related art.
The object of the present disclosure is achieved by a method for managing operation of a rail vehicle as disclosed herein.
The method includes identifying, by a first processing unit, a virtual subsystem for managing a specific operation of the rail vehicle from a plurality of virtual subsystems based on operational data associated with the rail vehicle. The method further includes generating one or more operational instructions capable of managing operation of the rail vehicle using the identified virtual subsystem based on a configuration of the rail vehicle. The method further includes initiating execution of the one or more operational instructions capable of managing operation of the rail vehicle, at system components configured for executing the one or more operational instructions.
The method may further include determining an anomaly in the operation of the rail vehicle based on the operational data. In one embodiment, determining the anomaly in the operation of the rail vehicle based on the operational data includes analyzing the operational data to determine deviation in values of one or more critical parameters with respect to a predefined range of values for the one or more critical parameters. Further, the anomaly is predicted based on the deviation in the values of the one or more critical parameters.
The method may further include determining a root cause of the anomaly in the operation of the rail vehicle using a root cause analysis technique. The method may further include predicting a safety risk associated with the anomaly in the operation of the rail vehicle. The method further includes determining one or more actions for mitigating the safety risk and generating operational instructions for implementing the one or more actions for mitigating the safety risk.
The method may further include determining a remaining life of the rail vehicle based on the anomaly in the operation of the rail vehicle. In one embodiment, the remaining life of the rail vehicle is determined based on a deviation in values of critical parameters from the predefined values or the predefined range of values. The method may further include optimizing a downtime of the rail vehicle by scheduling a maintenance activity for the rail vehicle based on the remaining life of the rail vehicle. The method may further include generating a report associated with the operation of the rail vehicle.
The object of the present disclosure is achieved by an apparatus including one or more first processing units, and a first memory unit communicatively coupled to the one or more first processing units. The first memory unit includes a management module stored in the form of machine-readable instructions executable by the one or more first processing units. The management module is configured to perform method acts described above.
Additionally, the object of the present disclosure is achieved by a system for managing an operation of the rail vehicle. The system includes one or more system components for providing operational data associated with the operation of the rail vehicle. The operational data includes values of parameters associated with the operation of the rail vehicle. The system further includes an apparatus as described above, communicatively coupled to the one or more system components. The apparatus is configured for managing operation of the rail vehicle based on the operational data according to the method described above.
In an embodiment, the system further includes an onboard unit located on the rail vehicle. The onboard unit includes a plurality of interfaces for communicating with the one or more system components and the apparatus for enabling the one or more system components communicate with the apparatus. The apparatus further includes one or more second processing units and a second memory communicatively coupled to the one or more second processing units. The second memory includes an offline emergency module stored in the form of machine-readable instructions executable by the one or more second processing units. The offline emergency module is configured for managing the operations of the rail vehicle when a communication between the onboard unit and the apparatus is interrupted.
The object of the present disclosure is achieved by a computer-program product having machine-readable instructions stored therein, which when executed by a processing unit, cause the processing unit to perform a method as describe above.
The realization of the disclosure by a computer program product and/or a computer-readable medium has the advantage that already existing management systems may be easily adopted by software updates in order to work as proposed by the disclosure.
The computer program product may be a computer program or include another element apart from the computer program. This other element may be hardware, (e.g., a memory device), on which the computer program is stored, a hardware key for using the computer program and the like, and/or software, (e.g., a documentation or a software key for using the computer program).
The above-mentioned attributes, features, and advantages of this disclosure and the manner of achieving them, will become more apparent and understandable with the following description of embodiments of the disclosure in conjunction with the corresponding drawings. The illustrated embodiments are intended to illustrate, but not limit the disclosure.
The present disclosure is further described hereinafter with reference to illustrated embodiments shown in the accompanying drawings, in which:
Hereinafter, embodiments for carrying out the present disclosure are described in detail. The various embodiments are described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details.
Referring to
According to an embodiment, the apparatus 105 may be an edge computing device. As used herein, “edge computing” refers to computing environment that is capable of being performed on an edge device (e.g., connected to the system components at one end and to a remote server(s) such as a computing server(s) or cloud computing server(s) on the other end), which may be a compact computing device that has a small form factor and resource constraints in terms of computing power. Alternatively, a network of the edge computing devices may also be used to implement the apparatus 105. Such a network of edge computing devices is referred to as a fog network.
In an embodiment, the apparatus 105 is a cloud computing system having a cloud computing-based platform configured to provide a cloud service for managing operation of the rail vehicle 102. As used herein, “cloud computing” refers to a processing environment including configurable computing physical and logical resources, for example, networks, servers, storage, applications, services, etc., and data distributed over the network, for example, the internet. The cloud computing platform may be implemented as a service for managing operation of rail vehicles. In other words, the cloud computing system provides on-demand network access to a shared pool of the configurable computing physical and logical resources. The network 115 is, for example, a wired network, a wireless network, a communication network, or a network formed from any combination of these networks.
In the present embodiment, the onboard unit 110 is communicatively coupled to the apparatus 105 through a network 115. The onboard unit 110 may connect to the network 115 through one or more access points (not shown). In one embodiment, the one or more access points may be located on, e.g., the rail vehicle 102-1, henceforth referred as rail vehicle 102. In another embodiment, the one or more access points may be located along the wayside of a railway track over which the rail vehicle 102 moves. For example, the access point may be integrated into a wayside signaling unit. The network 115 may be based on 5G communication, Wi-Fi communication, Microwave channel communication or a combination thereof.
The system components may include, but not be limited to, equipment onboard the rail vehicle 102 and track equipment such as balises and wayside units. In one embodiment, the system components are configured for communicating with each other, in addition to communicating with the apparatus 105, over the network 115. The equipment on the rail vehicle 102 may communicate with equipment on other rail vehicles, track equipment, and the apparatus 105. More specifically, the system components within the rail vehicle 102 may communicate with each other using, for example, a Train Communication Network (TCN) based on Ethernet technology or using Radio communication. The system components on the rail vehicle 102 may communicate with track equipment or equipment on other rail vehicles based on, for example, Train-to-Wayside Communication (TWC) based on GSM technology, WLAN, satellite communication, and so on. Similarly, the system components may communicate with the apparatus 105 using wireless communication technologies such as Wi-Fi, satellite communication, radio communication, microwave channel communication, cellular communication, and so on. In another embodiment, the communication between the system components may be controlled by the apparatus 105, for example, using cloud communications.
The apparatus 105 may be a (personal) computer, a workstation, a virtual machine running on host hardware, a microcontroller, or an integrated circuit. As an alternative, the apparatus 105 may be a real or a virtual group of computers (the technical term for a real group of computers is “cluster”, the technical term for a virtual group of computers is “cloud”).
The apparatus 105 includes a first communication unit 120, one or more first processing units 125, a first display 130, a first Graphical User Interface (GUI) 135, a first memory 140, and a database 145 communicatively coupled to each other. In one embodiment, the first communication unit 120 includes a transmitter (not shown), a receiver (not shown) and Gigabit Ethernet port (not shown). The first memory 140 may include 2 Giga byte Random Access Memory (RAM) Package on Package (PoP) stacked and Flash Storage. The one or more first processing units 125 are configured to execute the defined computer program instructions in the modules. Further, the one or more first processing units 125 are also configured to execute the instructions in the first memory 140 simultaneously.
The first processing unit 125 may include any type of computational circuit including, but not limited to, a microprocessor, microcontroller, complex instruction set computing microprocessor, reduced instruction set computing microprocessor, very long instruction word microprocessor, explicitly parallel instruction computing microprocessor, graphics processor, digital signal processor, or any other type of processing circuit. The first processing unit 125 may also include embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, and the like. The first processing unit 125 may include hardware elements and software elements. The first processing unit 125 may be configured for multithreading that is hosting different calculation processes at the same time and executing them either in parallel or switching between active and passive calculation processes.
The first display 130 includes a High-Definition Multimedia Interface (HDMI) display and a cooling fan (not shown). Additionally, control personnel may access the apparatus 105 through the first GUI 135. The first GUI 135 may include a web-based interface, a web-based downloadable application interface, and so on.
The database 145 may store data logs associated with the operation of the rail vehicle 102. The data logs may include values of parameters associated with the operation of the rail vehicle 102, along with corresponding time stamps. In addition, the database 145 may also store information associated with route information of the rail vehicle 102, diagnostics associated with the rail vehicle 102, maintenance activities performed on the rail vehicle 102, and so on. In one implementation, the database 145 may be stored in the first memory 140. In another embodiment, the database 145 may be stored on a database server (not shown).
The first memory 140 may be one of a volatile memory and a non-volatile memory. The first memory 140 may be coupled for communication with the first processing unit 125. The first processing unit 125 may execute machine-readable instructions and/or code stored in the first memory 140. A variety of computer-readable storage media may be stored in and accessed from the first memory 140. The first memory 140 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.
In the present embodiment, the first memory 140 further includes a management module 148. The execution of the management module 148 may also be performed using co-processors such as Graphical Processing Unit (GPU), Field Programmable Gate Array (FPGA), or Neural Processing/Compute Engines. The management module 148 includes a communication module 150, a core manager module 152, a configuration module 154, a data analysis module 156, a data logging module 158, and a report generation module 160 as shown in
The communication module 150 is configured for managing communication between the apparatus 105 and the onboard unit 110. For example, the communication module 150 may control the first communication unit 120 of the apparatus 105 for communicating with the onboard unit 110 over the network 115. In addition, the communication module 150 may also preprocess the operational data received from the onboard unit 110 by performing operations such as data conversion, filtering, smoothening, and so on. Further, the communication module 150 may route the preprocessed data to one or more modules of the apparatus 105 based on the source or value of parameters present in the operational data.
The core manager module 152 is configured to handle operational data received from the plurality of onboard units 110. In one example, the core manager module 152 may segregate the operational data received from each onboard unit among the plurality of onboard units 110. Upon segregation, the core manager module 152 may identify a virtual subsystem based on the type or source of the operational data or based on output of another virtual subsystem. The term ‘virtual subsystem’, as used herein, may refer to a virtual machine that emulates functionalities of logical components of a physical subsystem used for managing the operation of the rail vehicle 102. More specifically, the operational data associated with non-vital functions are provided to the virtual ATO subsystem 166 and the operational data associated with vital functions are provided to the virtual ATP subsystem 168. The vital functions may include enforcing compliance with speed restrictions or signals. The non-vital functions may include functions that are otherwise performed by a driver of the rail vehicle 102, for example, maintaining accurate stopping position at railway stations, controlling of platform screen doors at railway stations, opening and closing of doors on the rail vehicle 102, operation of lights, triggering announcements or alarms, and so on. In one example, track coordinates obtained from balises may be provided to the virtual ATP subsystem 168, based on which the virtual ATP subsystem 168 may determine whether brakes are to be applied or if the rail vehicle 102 should continue moving, so as to comply with a speed or signal restrictions associated with a location of the rail vehicle 102. The virtual ATP subsystem 168 may further generate digital outputs to indicate whether the rail vehicle 102 should continue to move or apply brakes and corresponding operational instructions. In another example, the speed of the rail vehicle 102 received from radar system 190-3 may be given to the virtual ATO subsystem 166. The virtual ATO subsystem 166 may further determine a rate of acceleration or deceleration required for controlling the speed of the train. The virtual ITF subsystem 170 may generate operational instructions for controlling radio communications between system components and also between one or more system components and the onboard unit 110.
The configuration module 154 is configured to modify the one or more operational instructions generated based on a configuration associated with the rail vehicle 102. The configuration of the rail vehicle 102 may be based on format of ‘ini’ files or other similar initialization files used in configuring the software associated with one or more system components on the rail vehicle 102. In addition, the configuration may also be based on the hardware associated with the system components, e.g., number of onboard units on the rail vehicle 102.
The data logging module 158 may log the operational data received from the onboard unit 110 to the database 145. The operational data may be logged based on, for example, timestamps associated with the operational data, an identity associated with the onboard unit 110 or the rail vehicle 102, and so on.
The data analysis module 156 may analyze the operational data to determine trends or patterns associated with the operational data. Further, the data analysis module 156 may draw inferences from the operational data based on the analysis of the operational data. The analysis may be performed based on descriptive techniques, exploratory techniques, inferential techniques, predictive techniques, causal techniques, qualitative analysis techniques, quantitative analysis techniques, and so on. The inferences drawn based on the analysis may be associated with a health condition of the rail vehicle 102, a remaining life of the rail vehicle 102, anomalies associated with the operation of the rail vehicle 102, scheduling of maintenance activities for the rail vehicle 102, and so on.
The report generation module 160 may generate reports associated with the operation of the rail vehicle 102. The report may include information such as values of parameters associated with the operation of the rail vehicle 102, anomalies detected, remaining life of the rail vehicle 102, maintenance activities scheduled, the optimized downtime estimated, operational instructions provided to the system components, an outcome of providing the operational instructions to the system components, and so on. The report may include both text and graphical representations such as charts, graphs, tables, and so on. In one example, the report may be updated continuously in real-time. In another example, the report may be generated periodically, (e.g., every 15 minutes). The generated report may be further transmitted to a display unit. The display unit may be associated with service personnel, railway personnel, regulatory authorities, and so on, and may be installed on the rail vehicle 102 or at a remote location. The display unit may be part of a personal computer, a workstation, a Human-Machine Interface, a personal digital assistant, and so on. The reports may be include details such as health condition of the rail vehicle 102 along with an associated time-stamp, a remaining life of the rail vehicle 102, anomalies in the operation of the rail vehicle 102, maintenance activities scheduled, an optimized downtime of the rail vehicle 102 if the maintenance activities are performed, and so on. The reports generated by the report generation module 160 may be further displayed to an end user, on a web user interface associated with the first GUI 135.
Those of ordinary skilled in the art will appreciate that the hardware depicted in
A system in accordance with an embodiment of the present disclosure includes an operating system employing a graphical user interface. The operating system permits multiple display windows to be presented in the graphical user interface simultaneously with each display window providing an interface to a different application or to a different instance of the same application. A cursor in the graphical user interface may be manipulated by a user through the pointing device. The position of the cursor may be changed and/or an event such as clicking a mouse button, generated to actuate a desired response.
One of various commercial operating systems, such as a version of Microsoft Windows™ may be employed if suitably modified. The operating system is modified or created in accordance with the present disclosure as described.
The present disclosure is not limited to a particular computer system platform, processing unit, operating system, or network. One or more aspects of the present disclosure may be distributed among one or more computer systems, for example, servers configured to provide one or more services to one or more client computers, or to perform a complete task in a distributed system. For example, one or more aspects of the present disclosure may be performed on a client-server system that includes components distributed among one or more server systems that perform multiple functions according to various embodiments. These components include, for example, executable, intermediate, or interpreted code, which communicate over a network using a communication protocol. The present disclosure is not limited to be executable on any particular system or group of system, and is not limited to any particular distributed architecture, network, or communication protocol.
Referring to
The second processing unit 175, as used herein, refers to any type of computational circuit, such as, but not limited to, a microprocessor, microcontroller, complex instruction set computing microprocessor, reduced instruction set computing microprocessor, very long instruction word microprocessor, explicitly parallel instruction computing microprocessor, graphics processor, digital signal processor, or any other type of processing circuit. The second processing unit 175 may also include embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, and the like. The second processing unit 175 may include hardware elements and software elements. The second processing unit 175 may be configured for multithreading for hosting different calculation processes at the same time and executing the either in parallel or switching between active and passive calculation processes.
The second memory 180 may be volatile memory and non-volatile memory. The second memory 180 may be coupled for communication with the second processing unit 175. The second processing unit 175 may execute machine-readable instructions and/or code stored in the second memory 180. A variety of computer-readable storage media may be stored in and accessed from the second memory 180. The second memory 180 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.
The onboard unit 110 further includes a plurality of Input/Output (I/O) interfaces 185-1, 185-2 . . . 185-9 for receiving operational data associated with the rail vehicle 102 from system components 190-1, 190-2 . . . 190-3 (henceforth collectively referred as system components 190) in real-time and for providing operational instructions, generated by the apparatus 105, to the system components 190 for execution at the system components 190. For the sake of brevity and for ease of explanation, the present embodiment is explained by considering a Human Machine Interface (HMI) 190-1, a Juridical Recording Unit (JRU) 190-2, a radar system 190-3, a Odometer Pulse Generator (OPG) 190-4, a balise 190-5, a Passenger Information System/Transit Management System (PIS/TMS) 190-6, a diagnostics system 190-7, driver's cab controls 190-8, and a train control 190-9 as the system components 190. Accordingly, the plurality of I/O interfaces 185-1, 185-2 . . . 185-9 include a Human Machine Interface (HMI) interface 185-1, a Juridical Recording Unit (JRU) interface 185-2, radar interface 185-3, Odometer Pulse Generator (OPG) interface 185-4, a balise interface 185-5, a Passenger Information System/Transit Management System (PIS/TMS) interface 185-6, a diagnostics interface 185-7, a driver's cab interface 185-8, and a train control interface 185-9. Each of the I/O interfaces 185-1, 185-2 . . . 185-9 may include a transmitter (not shown), a receiver (not shown), and a communication port (not shown) that enables the onboard unit 110 to communicate with the respective system component.
The HMI interface 185-1 is configured to enable the onboard unit 110 to communicate with the HMI 190-1 on the rail vehicle 102. The onboard unit 110 may receive inputs or control commands provided by a driver the HMI 190-1, over the HMI interface 185-1. The onboard unit 110 may also provide feedbacks to the driver through the HMI 190-1, over the HMI interface 185-1. In one example, the HMI 190-1 may be an LCD touch screen for receiving touch gestures. For example, the human operator may provide touch gestures for changing a mode of operation of the rail vehicle 102 from manual to semi-automatic. The LCD touch screen may also provide visual indications relating to a status of operation of the rail vehicle 102. For example, the status may include a speed of the rail vehicle 102, a permitted speed of the rail vehicle 102, an upcoming station, an estimated time of arrival at the upcoming station and so on. The visual indications may also relate to alarms or instructions to the driver of the rail vehicle 102.
The Juridical Recording Unit (JRU) interface 185-2 is configured to enable the onboard unit 110 to communicate with the JRU 190-2. The JRU 190-2 is a device which facilitates collecting, storing, and retrieving vital information associated with the rail vehicle 102. The vital information may include audio and video signals related to events associated with the rail vehicle 102. For example, the video signals are collected from CCTV units installed across the rail vehicle 102. The onboard unit 110 may store and retrieve information stored in the JRU 190-2, through the JRU interface 185-2.
The radar interface 185-3 is configured to enable the onboard unit 110 to receive a speed of the rail vehicle 102 from the radar system 190-3. In one example, the radar system 190-3 may be mounted on the rail vehicle 102 and is configured to measure a speed of the rail vehicle 102, for example, based on Doppler effect.
The Odometer Pulse Generator (OPG) interface 185-4 is configured to enable the onboard unit 110 to communicate with the OPG 190-4. The OPG 190-4 may be located on an axle of the rail vehicle 102 and may measure a distance covered by the rail vehicle 102.
The balise interface 185-5 is configured to enable the onboard unit 110 to communicate with at least one of a balise transmission module provided on the rail vehicle 102 or a balise 190-5 provided on the railway track. Each balise may be associated with unique track coordinates, that enable the onboard unit 110 to determine an accurate location of the rail vehicle 102.
The Passenger Information System/Transit Management System (PIS/TMS) interface 185-6 is configured to enable the onboard unit 110 to communicate with the PIS/TMS 190-6. In one example, the PIS/TMS interface 185-6 receives operational data such as distance to an upcoming station, estimated time of arrival at the upcoming station, duration of stoppage at the upcoming station from the PIS/TMS 190-6.
The diagnostics interface 185-7 is configured to enable the onboard unit 110 to communicate with the diagnostics system 190-7 on the rail vehicle 102. The diagnostics system 190-7 may record and store diagnostic information such as faults associated with the rail vehicle 102, operational data associated with the rail vehicle 102, correlations between the faults, an operating state of the rail vehicle 102, and so on.
The driver's cab interface 185-8 is configured to enable the onboard unit 110 to communicate with the driver's cab control 190-8 provided in the driver's cab. For example, the onboard unit 110 may receive operational data associated with the driver's cab control 190-8 associated with opening and closing of doors, operation of lights, communication systems and so on. In another example, the operational data may include a mode of operation of the rail vehicle 102. The mode of operation may be one of manual, automatic, fully automatic, semi-automatic, and extended automatic.
The train control interface 185-9 is configured to enable the onboard unit 110 to communicate with one or more train controls 190-9. The train controls 190-9 is configured for providing control signals for driving the rail vehicle 102 and also for actuating brakes. The brakes may include an electric braking system for primary braking and a pneumatic braking system for standby or secondary purposes. In addition to the above, the second memory 180 includes an offline emergency module 195. The offline emergency module 195 includes a set of machine-readable instructions, which when executed by the processor, manages an operation of the rail vehicle 102 when a communication between the onboard unit 110 and the apparatus 105 is interrupted, for example, when the rail vehicle 102 passes through a tunnel. In one embodiment, the onboard unit 110 may manage the operation of the rail vehicle 102, when the communication is interrupted, based on previously stored operational instructions. In one example, the onboard unit 110 may provide an indication to the driver to switch to manual mode from auto mode when the communication is interrupted. In another example, the onboard unit 110 may automatically degrade the mode of operation of the rail vehicle 102 when the communication is interrupted. In another example, the onboard unit 110 may instruct another onboard unit, in another railcar on the rail vehicle 102, to communicate with the apparatus 105 for managing the operation of the vehicle. In yet another example, the onboard unit 110 may activate an emergency braking system when the communication with the apparatus 105 is disrupted. In another embodiment, the onboard unit 110 may use operational data captured immediately before the disruption of the communication, to generate operational instructions to be executed by the system components. The second memory 180 may also store predefined operational instructions to be executed when the communication between the onboard unit 110 and the apparatus 105105 is interrupted. For example, one of the predefined operational instructions may be associated with downgrading a mode of operation of the rail vehicle 102, (e.g., from automatic to manual mode).
Referring to
At act 205, a virtual subsystem for managing a specific operation of the rail vehicle 102 is identified from a plurality of virtual subsystems based on operational data associated with the rail vehicle 102. The operational data includes values of parameters associated with the operation of the rail vehicle 102. The operational data is obtained from one or more system components in real-time. The system components may refer to any remotely located equipment that is configured for communicating with the first processing unit 125. The equipment may include track equipment and rail equipment. The track equipment may include equipment installed on or along the railway track and may include balises, wayside signaling units, interlocking systems, and so on. The rail equipment may include equipment on the rail vehicle 102 and may include sensing units, pantograph systems, braking systems, radio communication systems, onboard units, Juridical Recording Units (JRU), radar systems, odometry circuits, axle accelerometers, driver cab controls, and so on. The rail equipment may be associated with the rail vehicle 102 that is being managed or another rail vehicle, for example, a rail vehicle running on a parallel track. In addition to track equipment and rail equipment, the system components may also include equipment such as transponders installed at facilities associated with railway regulatory authorities or at railway stations. Further, the operational data may also be generated by another virtual subsystem.
The operational data includes values of parameters associated with the operation of the rail vehicle 102. The parameters associated with the operation of the rail vehicle 102 may include any parameter that indicates an operating condition of the rail vehicle 102. For example, the parameters associated with the operation of the rail vehicle 102 may relate to a speed of the rail vehicle 102, a permitted speed of the rail vehicle 102, geographical position of the rail vehicle 102, distance covered by the rail vehicle 102 from a starting point, upcoming stations, distance of the rail vehicle 102 to an upcoming station or a stopping point, stoppages, number of brakings, direction of the rail vehicle 102, signals followed by the rail vehicle 102, a mode of operation of the rail vehicle 102, status of communication interfaces on the rail vehicle 102, operational status of digital inputs and outputs related to fans, lamps and doors, and so on.
In one example, the values of the parameters may be directly measured as numerical values, for example, speed and distance. In another example, the values of the parameters may not be directly measured as numerical values but may be converted to numerical values using a suitable coding system. For example, the mode of operation of the rail vehicle 102 may be one of manual, automatic, semi-automatic, or extended automatic. Each of the modes of operation may be assigned a numerical code, (e.g., manual is 0, semi-automatic is 1, automatic is 2, and extended automatic is 3). In one example, the identified virtual subsystem is associated with one or more vital functions for providing safety of the rail vehicle 102. In another example, the identified virtual subsystem may be associated with one or more non-vital functions. In yet another example, the identified virtual subsystem may be associated with communication-related functions. The communication-related functions may include controlling of radio-based communication interfaces between system components or between the system component and the first processing unit 125.
In one embodiment, the virtual subsystem may be identified based on a source of the operational data. For example, if the operational data is obtained from the balise, then the virtual subsystem associated with vital functions may be identified. In another embodiment, the virtual subsystem may be identified based on the type of operational data. For example, if the operational data is associated with status of a communication interface on the rail vehicle 102, then the virtual subsystem associated with communication related functions may be identified. In yet another embodiment, the virtual subsystem may be identified based on a value of the parameter that is associated with the operational data. For example, if the speed of the rail vehicle 102 is less than the permitted speed for the rail vehicle 102, then the virtual subsystem associated with non-vital functions may be identified. Otherwise, the virtual subsystem associated with vital functions may be identified. In yet another embodiment, the virtual subsystem associated with non-vital functions is triggered based on an output of the virtual subsystem associated with vital functions.
At act 210, one or more operational instructions capable of managing operation of the rail vehicle 102 are generated, using the identified virtual subsystem, based on a configuration of the rail vehicle 102. The configuration of the rail vehicle 102 may be based on several factors such as length of the rail vehicle 102, number of rail cars (or couplings) on the rail vehicle 102, mode of operation of the rail vehicle 102, a type of service associated with the rail vehicle 102, an OEM associated with the rail vehicle 102, hardware and associated software used on the rail vehicle 102, communication protocols used by the hardware to communicate with system components, and so on. In one example, the configuration of the rail vehicle 102 may be prestored in the database 145. Further, the prestored configuration of the rail vehicle 102 may be fetched for generating the one or more operational instructions, based on an identity of the rail vehicle 102. In another example, the configuration of the rail vehicle 102 may be determined on an ad hoc basis, based on the operational data associated with the rail vehicle 102.
At act 215, execution of the one or more operational instructions capable of managing operation of the rail vehicle 102, is initiated at system components 190 configured for executing the one or more operational instructions. The system components 190 are located remotely from the first processing unit 125, that is the apparatus 105. In one example, the one or more operational instructions may be associated with controlling a speed of the rail vehicle 102 by decelerating the rail vehicle 102 through the application of brakes. In another example, the one or more operational instructions may be associated with opening of doors for deboarding passengers at a railway station, upon stopping the rail vehicle 102 at the appropriate position.
Referring to
Further, one or more actions for mitigating the safety risk are determined and operational instructions for implementing the one or more actions for mitigating the safety risk are generated. The operational instructions for executing the one or more actions for mitigating the safety risk may be generated by the virtual subsystem identified based on the operational data. The operational instructions may be executed at the rail vehicle 102, by the system components, in order to mitigate the safety risk. The method includes acts 305-325. In one embodiment, the method 300 is implemented using the apparatus 105.
At act 305, an anomaly in the operation of the rail vehicle 102 based on the operational data is determined by firstly analyzing the operational data with respect to deviation in values of one or more critical parameters with respect to a predefined range of values for the one or more critical parameters. The term ‘anomaly’ may refer to a deviation in normal operation of any component of the rail vehicle 102. The component of the rail vehicle 102 may be an electrical component, an electronic component, a mechanical component, an electromechanical component, and so on. In one example, the anomaly in the operation of the rail vehicle 102 may be associated with Heating, Ventilation and Air-Conditioning (HVAC) in the rail vehicle 102. In another example, the anomaly may be in the form of heating up of a component of the rail vehicle 102. In yet another example, the anomaly may be in the form of fuse failure. In yet another example, the anomaly may be in the form of a large speed difference along an axle, with respect to a predefined maximum speed difference. In yet another example, the anomaly may be in the form of an abnormal speed measured on by an axle accelerometer. In yet another example, the anomaly may be associated with logging of data associated with the operation of the rail vehicle 102. In yet another example, the anomaly may be in the form of abnormal noises. In yet another example, the anomaly may be in the form of abnormal vibrations. In yet another example, the anomaly may be in the form of malfunctioning or non-functioning of a component of the rail vehicle 102.
Further, deviation in the values of one or more critical parameters with respect to a predefined range of values for the one or more critical parameters is determined. The critical parameters may include, but not limited to, speed, velocity, acceleration, temperature, pressure, vibration, friction, noise, frequency, and so on. For example, the speed of the rail vehicle 102 for normal operation may be in the range of 150 kmph to 200 kmph. If the speed of the rail vehicle 102 measured by axle accelerometers is greater than 200 kmph, then the rail vehicle 102 is associated with the anomaly of abnormal speed. In yet another example, if the temperature of a mechanical component is greater than a predefined temperature, (e.g., 50° C.), then the rail vehicle 102 is associated with the anomaly of abnormal heating of the mechanical component. The deviation in the values of the critical parameters may also be based on Railway Safety Regulations defined for a territory in which the rail vehicle 102 operates.
Based on the deviation in the values of the one or more critical parameters, the anomaly in the operation of the rail vehicle 102 is determined. For example, assume that the anomaly is heating of an axle box present on the rail vehicle 102. The anomaly may be determined by comparing a temperature of the axle to a predefined temperature. The temperature on the axle may be measured using an infrared sensor and transmitted to the apparatus 105 over the onboard unit 110. Further, if the measured temperature of the axle is greater than the predefined temperature, then the rail vehicle 102 may be associated with the anomaly of overheating of the axle.
At act 310, a root cause associated with the anomaly in the operation of the rail vehicle 102 is determined using a root cause analysis technique. The root cause may be defined as any factor that causes the anomaly in the operation of the rail vehicle 102. For example, the root cause may be associated with lack of lubrication, wear and tear of components, improper coupling of components, electrical faults, improper control commands given by a driver, faulty signaling, and so on. The root cause may be determined based on a type of the anomaly by using any known root cause analysis technique. In one example, the root cause analysis technique may employ root cause analysis models such as Neural Networks, Bayesian network classifiers, Support Vector Machines (SVMs) and so on, for inferring the root cause based on the type of anomaly. Alternatively, the root cause may also be determined using root cause analysis techniques such as fault-tree analysis, failure mode and effects analysis and so on. In addition to determining the root cause, a location of the root cause may also be identified using the root cause analysis technique. For example, the root cause associated with the anomaly may be determined using a neural network model. The neural network model may be pre-trained using deviation data associated with one or more rail vehicles to determine the root cause. The root cause may be identified as, for example, lack of lubrication in a wheel bearing mounted on the axle.
At act 315, a safety risk associated with the anomaly in the operation of the rail vehicle 102 is predicted. The safety risk may be predicted based on a risk indicator value determined from the operational data. For example, if the risk indicator value is greater than, (e.g., 8), the safety risk may be associated with derailment of the rail vehicle 102.
At act 320, one or more actions for mitigating the safety risk are determined. The one or more actions may include, but is not limited to, engaging emergency brakes, triggering alarms, and so on. The one or more actions may also include transmitting notifications including recommendations or instructions for the driver or other railway authorities. The recommendations may include checks or measures to be taken in order to alleviate the safety risk. For example, the recommendation may include a nearest stoppage and a suggestion to stop at the nearest stoppage to replace or repair a faulty component. In another example, the rail vehicle 102 may be operating in automatic mode and the recommendations may include acts that the driver may take in order to avoid the safety risk. For example, firstly the driver may be asked to change the mode of operation from automatic mode to manual mode. Further, the driver be asked to check for an indication on a control panel inside the rail vehicle 102. Further, if the indication is present, the driver may be provided with one or more further acts to be performed to avoid the safety risk. For example, the one or more actions may include lubricating the wheel bearing.
At act 325, operational instructions for implementing the one or more actions for mitigating the safety risk are generated. For example, the operational instructions may be associated with displaying a notification indicating the safety risk and one or more recommendations for mitigating the safety risk on the HMI 190-1. The one or more recommendations for mitigating the safety risk may be prestored in the database 145. For example, the recommendations may include lubricating the wheel bearing at an upcoming stoppage. The operational instructions are further transmitted to the onboard unit 110. The onboard unit 110 may further display the notification on the HMI 190-1.
Referring to
At act 405, an anomaly in the operation of the rail vehicle 102 is determined.
At act 410, a remaining life of the rail vehicle 102 is determined based on the anomaly in the operation of the rail vehicle 102. For example, a condition indicator may be calculated based on the deviation in values of critical parameters. Further, the condition indicators may be fit into a degradation model in order to determine the remaining life of the rail vehicle 102. In one example, the remaining life of the rail vehicle 102 may be determined in terms of remaining life of a critical component, (e.g., an axle), of the rail vehicle 102. The term ‘critical component’ as used herein may refer to any component which upon failure results in high safety risk for the rail vehicle 102.
In another embodiment, data logs associated with the operational data, maintenance history, operating conditions, operating history, age of components, and so on, may also be used for determining the remaining life of the rail vehicle 102, for example, using statistical techniques such as regression. Alternatively, or in addition to the data log associated with the rail vehicle 102, data logs associated with other similar rail vehicles may also be used for determining the remaining life of the rail vehicle 102. In one example, the other similar rail vehicles may include rail vehicles having components manufactured by the same Original Equipment Manufacturer (OEM) as the components of the rail vehicle 102. In another example, the other similar rail vehicles may include rail vehicles having similar configuration as the rail vehicle 102. In yet another example, the other similar rail vehicles may include rail vehicles that are operating under similar operating conditions, for example, operating on the same route or for the same service (mass transit, mainline transit, freight) and so on. Further, hazard models and probability distributions associated with failure times of components of the rail vehicle 102 are used to determine the remaining life of the rail vehicle 102 based on the data logs. In yet another embodiment, the remaining life of the rail vehicle 102 may be determined based on run-to-failure data associated with different components of the rail vehicle 102. The run-to-failure data may be obtained from other components exhibiting similar behavior as the components of the rail vehicle 102. Further, degradation profiles of the other components are determined based on the run-to-failure data. Further, the operational data or other data in the data logs associated with the rail vehicle 102 is compared with the degradation profiles in order to identify the closest matching degradation profile. Further, the closest matching degradation profile is used to determine the remaining life of the rail vehicle 102.
In one embodiment, the remaining life of the rail vehicle 102 may be determined based on the data logged by the data logging module 158. More specifically, the remaining life is determined based on hazard models and probabilistic distributions associated with failure times of critical components, available from maintenance data in the data logs. For example, the failure times of a critical component may be determined using bath-tub degradation models, the failure time of another critical component may be based on Poisson's distribution and so on. Further, the remaining life of the rail vehicle 102 may be determined based on, for example, the shortest failure time among all the critical components of the rail vehicle 102.
At act 415, a downtime of the rail vehicle 102 is optimized by scheduling a maintenance activity for the rail vehicle 102 based on the remaining life of the rail vehicle 102. The maintenance activity of the rail vehicle 102 may be scheduled when the remaining life of the rail vehicle 102 is, e.g., 30 days. The downtime of the rail vehicle 102 be estimated based on factors, including but not limited to, a geographical location of the rail vehicle 102, a type of service associated with the rail vehicle 102, anomalies associated with the operation of the rail vehicle 102, root causes associated with the anomalies, availability of spares and service personnel and so on. The geographical location of the rail vehicle 102 may be used to determine a distance to a nearest depot where the rail vehicle 102 may be taken for maintenance. The type of service may be used to determine a frequency of operation of the rail vehicle 102 and an associated time schedule of the operation. The anomalies and the root causes associated with the anomalies may be used to estimate an actual repair time or a maintainability of the rail vehicle 102 during the downtime. For example, replacement of a component may take less time compared to repairing the component.
The availability of spares and service personnel may be used to schedule the maintenance activity. For example, if the spares are unavailable, then the probability that the spares may be procured before the start of the maintenance activity may also be considered for determining the downtime. In one aspect of the present disclosure, the service personnel may also be informed to procure the spares before the start of the maintenance activity by sending a notification to an electronic device (not shown) associated with the service personnel. The electronic device may be a mobile phone, a personal computer, a tablet, and so on. The notification may be sent a predefined number of days, (e.g., 20 days), ahead of the maintenance activity so as to enable the service personnel to procure the spares. Similarly, the service personnel may receive multiple notifications for procuring spares associated with one or more rail vehicles. In addition, the notifications may also include web links to sources for procuring the spares. The web links may be selected and added to the notification based on, for example, the type of spares required. In another example, the maintenance activity may be scheduled based on availability of the service personnel for performing the maintenance activity. Based on the above factors, the maintenance activity may be scheduled before the remaining life of the rail vehicle 102 is exhausted, in order to optimize the downtime.
For example, assume that the remaining life of the wheel-bearing is 28 days. The downtime may be optimized by scheduling the maintenance activity based on availability of spare wheel-bearings and service personnel. If the spare wheel-bearings are readily available and the service personnel are free from, e.g., 3 pm to 5 pm on the same day, and an actual repair time required for replacing the wheel-bearing is 30 mins, then the maintenance activity may be scheduled for the time between 3 pm to 4 pm on the same day. However, if the spare wheel-bearings are unavailable, then the apparatus 105 may transmit a notification to an electronic device of the service personnel to procure the spare wheel-bearings, for example, using a trade portal link associated with sellers of wheel-bearings that is sent along with the notification. Further, the maintenance activity may be scheduled after an estimated time of arrival of the provided on the trade portal link, after the service personnel places an order for the wheel-bearing on the trade portal, and an availability of the service personnel, before the remaining life of the wheel-bearing on the rail vehicle 102 is exhausted.
Referring to
At act 505, the apparatus 105 receives the operational data associated with the rail vehicle 102 from the onboard unit 110 located on the rail vehicle 102. The operational data is obtained from the system components 190 communicatively coupled to the onboard unit 110. In the present example, the operational data includes the speed of the rail vehicle 102 received from the radar system 190-3 and a permitted speed of the rail vehicle 102 as received from wayside signaling units.
At act 510, the core manager module 152 identifies the virtual ATP subsystem 168 for controlling the of the rail vehicle 102 based on operational data associated with the rail vehicle 102. The core manager module 152 provides the distance covered by the rail vehicle 102, the speed of the rail vehicle 102, the permitted speed of the rail vehicle 102 and the position of the rail vehicle 102 to the virtual ATP subsystem 168.
At act 515, the virtual ATP subsystem 168 may determine whether the speed of the rail vehicle 102 is below the permitted speed of the rail vehicle 102. If the speed of the rail vehicle 102 is above the permitted speed or if the speed of the rail vehicle 102 is close to the permitted speed, then the virtual ATP subsystem 168 may generate one or more operational instructions for limiting the speed of the rail vehicle 102 based on the configuration of the rail vehicle 102. The one or more operational instructions may be for applying brakes.
At act 520, the one or more operational instructions are transmitted to the onboard unit 110. The onboard unit 110 may further provide control signals to a train control associated with braking, through the train control interface 185-9. The train control may further actuate a brake valve associated with a pneumatic or electric braking system for engaging the brakes.
Referring to
At act 605, apparatus 105 receives the operational data associated with the rail vehicle 102 from the onboard unit 110 located on the rail vehicle 102. The operational data may include the mode of operation received from the virtual ATP subsystem 168 of apparatus 105, track coordinates received from balise 190-5 on the railway track and also track data obtained from the track equipment such as wayside units or from the database 145. The track data may include information associated with a route to be followed by the rail vehicle 102.
At act 610, the core manager module 152 identifies a virtual subsystem for managing opening and closing of doors on the rail vehicle 102. In the present example, although the opening of doors is a non-vital function, it is necessary to provide that the doors of the rail vehicle 102 are not opened at positions that are unsafe for passengers boarding or deboarding the rail vehicle 102. Therefore, the core manager module 152 initially identifies the virtual ATP subsystem 168 for managing the opening of the doors of the rail vehicle 102.
At act 615, the virtual ATP subsystem 168 analyses the track data and the track coordinates to determines whether the doors may be opened. Further, the virtual ATP subsystem 168 generates a digital output based on the analysis of the track data and the track coordinates. More specifically, the virtual ATP subsystem 168 may generate a digital output indicating whether the doors may be opened or not. For example, assume that the virtual ATP subsystem 168 generates a digital output of ‘1’ indicating that the doors may be opened. The digital output of ‘1’ causes the virtual ATO subsystem 166 to be triggered for generating operational instructions for opening the doors.
At act 620, the operational instructions are transmitted to the onboard unit 110. The onboard unit 110 may further provide the operational instructions from the virtual ATO subsystem 166 to train control interface 185-9, for operating the doors on the rail vehicle 102. Similarly, the virtual ATO subsystem 166 may also provide operating instructions for synchronous operations of platform screen doors with the doors of the rail vehicle 102.
The apparatus 105 may also generate a report including values of parameters that are associated with the operational data, commands provided to the rail vehicle 102, anomalies detected, root causes of the anomalies, safety risks associated with the anomalies, actions taken for mitigating the safety risks, maintenance activities scheduled, an optimized downtime of the rail vehicle 102 based on the maintenance activities scheduled and so on. The report may be generated, for example, every 5 minutes of operation of the rail vehicle 102.
Advantageously, the present disclosure relates to virtualizing subsystems such as Automatic Train Operation (ATO), Automatic Train Protection (ATP) and so on, that are traditionally hardware-based subsystems. More specifically, in the present disclosure, logical components corresponding to traditional hardware-based subsystems are located as virtual subsystems at a remote location such as a cloud server. As a result, the virtual subsystems may be common to a plurality of rail vehicles, as opposed to the traditional use of separate hardware-based subsystems on each rail vehicle. Further, the virtual subsystems may be provided as a cloud-based service to railway operators, for managing operation of rail vehicles, wherein the railway operators may be charged for usage of the cloud-based service.
Advantageously, the virtualization of subsystems helps in centralized monitoring of the operation of the rail vehicle 102. Further, the virtualization of subsystems also facilitates easy remote troubleshooting for bug fixing and also in providing quick technical support.
Advantageously, the present disclosure helps in reducing the amount of hardware present on the rail vehicle 102 by providing only the necessary operational instructions required for execution at the system components, using the virtual subsystems, rather than having separate circuitry for generating the operational instructions on the rail vehicle 102.
Advantageously, the present disclosure enables determining the anomaly in the operation of the rail vehicle 102 without the need for performing physical tests on the rail vehicle 102.
Advantageously, the root cause of the anomaly may be predicted using root cause analysis techniques using the operational data acquired from the rail vehicle 102.
Advantageously, the present disclosure is capable of automatically providing operational instructions to the system components for safety risk mitigation without necessitating intervention by a human operator.
Advantageously, the present disclosure helps in optimizing the downtime of the rail vehicle 102, thereby providing maximized productivity of the rail vehicle 102.
Advantageously, the present disclosure reduces manual intervention required for managing the operation of the rail vehicle 102.
The present disclosure may take the form of a computer program product including program modules accessible from computer-usable or computer-readable medium storing program code for use by or in connection with one or more computers, processors, or instruction execution system. For the purpose of this description, a computer-usable or computer-readable medium is any apparatus that may contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium may be electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation mediums in and of themselves as signal carriers are not included in the definition of physical computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, random access memory (RAM), a read only memory (ROM), a rigid magnetic disk and optical disk such as compact disk read-only memory (CD-ROM), compact disk read/write, and DVD. Both processors and program code for implementing each aspect of the technology may be centralized or distributed (or a combination thereof) as known to those skilled in the art.
It is to be understood that the elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present disclosure. Thus, whereas the dependent claims appended below depend from only a single independent or dependent claim, it is to be understood that these dependent claims may, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or dependent, and that such new combinations are to be understood as forming a part of the present specification.
While the disclosure has been illustrated and described in detail with the help of the disclosed embodiments, the disclosure is not limited to the disclosed examples. Other variations may be deducted by those skilled in the art without leaving the scope of protection of the claimed disclosure.
| Number | Date | Country | Kind |
|---|---|---|---|
| 19306236.1 | Sep 2019 | EP | regional |
