Distributed bogie diagnostics for track monitoring

A method of monitoring a track using train cars includes collecting first sensor data corresponding to a track location by a first sensor network on a first train car. Based on the first sensor data, a potential track anomaly at the track location is identified by a diagnostics system on the first train car. A message describing the anomaly is transmitted to diagnostics systems located on other train cars. The message is received by a second diagnostics system on a second train car located behind the first train car. The second diagnostics system determines a time at which the second train car will be passing over track location and, at the determined time, collects second sensor data. If the track anomaly is present in both the first sensor data and the second sensor data at the track location, a train control system is notified of the track anomaly.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a national phase filing under 35 U.S.C. § 371 of International Patent Application No. PCT/US2017/052140, filed Sep. 19, 2017, which is incorporated herein by reference in its entirety.

TECHNICAL FIELD

The present invention relates generally to methods, systems, and apparatuses for monitoring track anomalies using plurality of bogie sensor systems installed on a plurality of train cars. The technology described herein may be used for track and bogie anomaly detection, as well as generating maps of tracks.

BACKGROUND

A bogie is the wheel chassis of a train on which the train wagon rides. A typical train wagon has two bogies. New bogie systems contain sensors to monitor the health of the bogie. Thus, for example, a bogie may have sensors to monitor the roundness of the wheels, the temperature of the axle box bearing and gearbox, shaft bending, resonances, oil temperature, oil level, and various vibration levels. The data collected by the sensor systems is used to detect damage to the bogie system in its early stages before mechanical failures occur. Using this information, parts can be repaired or replaced as necessary during maintenance of the train system. Although the bogie sensor systems collect a great deal of data, conventional systems typically operate independently and there is little or no collaboration between different sensor systems.

The bogie sensor system may also be used to monitoring the condition of the track on which the train rides. For example, if the bogie sensor system measures an unexpected shock or vibration at a particular location, it may label the location as having an anomaly. However, because of the lack of coordination and collaboration, it is challenging to determine whether the unexpected shock or vibration is the result of determination or failure of the bogie's mechanical system or whether there is a true anomaly in the track. Accordingly, it is desired to provide technology for enhanced detecting, classifying, and verification of anomalies that occur while the bogie is in motion.

SUMMARY

Embodiments of the present invention address and overcome one or more of the above shortcomings and drawbacks by providing methods, systems, and apparatuses related to a bogie monitoring system for detecting, classifying, and verifying anomalies in the bogie system itself, as well as anomalies on the track on which the train rides.

According to some embodiments, a method of monitoring a track using a train comprising a plurality of train cars includes collecting first sensor data corresponding to a track location by a first sensor network on a first train car and, based on the first sensor data, identifying a potential track anomaly at the track location by a first diagnostics system on the first train car. A message describing the anomaly is transmitted from the first diagnostics system to diagnostics systems located on one or more other train cars included in the train. The message comprises an indication of the track location. The message is received by a second diagnostics system on a second train car located behind the first train car with respect to the train's direction of travel. The second diagnostics system determines a time at which the second train car will be passing over track location and, at the determined time, collects second sensor data at the track location by a second sensor network on the second train car. If the track anomaly is present in both the first sensor data and the second sensor data at the track location, a train control system is notified of the track anomaly.

Various enhancements, refinements, and other modifications can be made to the aforementioned method in different embodiments. For example, in one embodiment, prior to collecting the second sensor data and in response to receiving the message, one or more of the following may occur: the sampling speed of the second sensor network on the second train car may be increased, data collection algorithms with functionality related to detection of the anomaly may be enabled, and/or data collection algorithms with functionality unrelated to detection of the anomaly may be disabled. In some embodiments, the track location is determined based on a Global Positioning System (GPS) signal received by the first diagnostics system on the first train car. In other embodiments, the train's sensors read location markings on the track and use the readings to determine track location.

According to other embodiments, a second method of monitoring a track using a train comprising a plurality of train cars includes collecting first sensor data corresponding to a track location by a first sensor network on a first train car. Based on the first sensor data, a potential track anomaly may be identified at the track location by a first diagnostics system on the first train car. The potential track anomaly is correlated (i.e., confirmed) based on second sensor data corresponding to the track location collected by a second sensor network on a second train car. Then, a map of the track is updated to indicate a track anomaly at the track location. In some embodiments, a train control system located on the train sends the map of the track to at least one system external to the train.

According to other embodiments, a system for diagnosing anomalies during operations of a train includes a plurality of bogie diagnostics computer systems distributed among a plurality of train cars included in the train. The bogie diagnostics computer system at each train car comprises one or more processors, a bogie interface, a plurality of analysis programs, and a diagnostics program. The bogie interface is configured to collect sensor data from each bogie coupled to the train car according to a sampling rate. The analysis programs are executable by the processors. These analysis programs comprise an anomaly detection program and one or more other programs. The anomaly detection program is configured to detect track anomalies based on the sensor data collected by the bogie interface. The diagnostics program is also executable by the processors and it controls operation of the analysis programs. The aforementioned system further includes a communication network connecting the plurality of bogie diagnostics computer systems.

In some embodiments of the aforementioned system, the diagnostics program is configured to increase the sampling rate of the anomaly detection program in response to receiving an anomaly detection message from at least one other bogie diagnostics computer system. Alternatively (or additionally), the diagnostics program may disable all analysis programs other than the anomaly detection program. In some embodiment, as anomalies are detected, the anomaly detection program transmits an anomaly detection message to each bogie diagnostics computer system in the train, for example, by a broadcast or multicast message.

Some embodiments of the aforementioned system further include a train control system. This system is configured to receive an anomaly detection message and anomaly confirmation message from bogie diagnostics systems on the train. In response to receiving the anomaly confirmation message, the train control system sends a notification of the track anomalies to at least one system external to the train.

DETAILED DESCRIPTION

The following disclosure describes the present invention according to several embodiments directed at methods, systems, and apparatuses related to a bogie monitoring system for detecting, classifying, and verifying anomalies that occur while the bogie is in motion. This bogie monitoring system includes a bogie diagnostics computer system installed at each train car. Each computer system is connected via a data network so that anomalies and other information can be shared. Location information (e.g., via GPS) is available for the position of the bogie (e.g., via a link to the train control system). By enabling the diagnostics computer systems to share data amongst each other, a more robust root cause analysis is possible. Moreover, with the technology described herein, no additional equipment other than the bogie diagnostics equipment is required to monitor the “health” of a train track.

FIG.1illustrates a system100for diagnosing anomalies during operations of a train, according to some embodiments. In this example, the train comprises three train cars105A,105B,105C running on a track115. Each train car105A,105B,105C is coupled to two bogies. Each bogie includes multiple sensors connected via a sensor network internal to the bogie. The types of sensors used in the sensor network may include, for example, capacitive sensors, piezoelectric sensors, piezoresistive sensors, or Microelectromechanical systems (MEMS) sensors. It should be noted that, although two sensors are shown in the illustration presented inFIG.1; however, in practice, the number of sensors may be much greater. For example, in one embodiment, each sensor network includes 20-30 sensors. The types of information collected by the sensors may include, for example, speed, acceleration, temperature, humidity, and vibration.

Each train car105A,105B,105C includes a bogie diagnostics computer system that collects sensor data from the sensor networks of its bogies. Based on the collected sensor data, the bogie diagnostics computer system detects anomalies on the track. If a bogie diagnostics computer system for one train car identifies an anomaly, it could be attributed to a failure in the bogie or a failure in the track. The bogie diagnostics computer system that detected the anomaly may then request the data for the specific track location where it detected the anomaly from other bogies. It can now correlate its result with the results from the other bogies. For example, if multiple bogie diagnostics computer systems identify the same characteristics, it is a strong indication, that the issue is in the track and not in the bogie.

The operational parameters of the bogie diagnostics computer system may include amongst other, the sensor data acquisition speed, the selection of algorithms that to do the analysis (e.g., which issues to detect) and the frequency of how often those algorithms run. The default parameters may be calibrated for optimal information gathering during normal operation. However, specific events may trigger a change in these parameters, to gather more precise information for that event. A change could be data collection with a higher frequency over a short period of time, even though it may not be sustainable for long because the unit does not have the CPU power or storage capacity for the analysis. For example, when the bogie diagnostics computer system of a leading train car detects an anomaly, it can ask the following bogies to temporarily reconfigure its system to look for a specific aspect when the bogie drives over the specify location on the tack (e.g., at 200 kph and a train of 300 m the last bogie will cross the location of the first bogie 3.6 s later). The reconfiguration may include disabling some algorithms, changing the sample speed of the data, or running certain algorithms more often.

Bogie characteristics change over time (e.g., diameter of wheel due to abrasion and resurfacing). Some or all of that information may not be available on the bogie diagnostics computer system, mostly due to additional complexity which would impose on maintenance. However, this information can be reconstructed by comparing the signals of the different bogies with each other. For example, the new wheel diameter can be identified by the computer when it requests the current rotations per minute (RPM) of the axis of the other bogies and compares those values with its own.

A train control system is located in the first train car105A. The train control system generally performs various functions related to controlling the train operation. For the purpose of anomaly detection, the train control system receives anomaly detection messages from bogie diagnostics computer systems. The train control system also receives confirmation messages from bogie diagnostics computer systems that confirm the original anomaly detection. In response to receiving the confirmation message, the train control system may perform operations such as sending a notification of the track anomalies to at least one system external to the train. Also, as described in further detail below, in some embodiments, the train control system may generate a map of the track with the detected anomalies.

The bogie diagnosis computer systems and the train control system are all connected via communications network110. This communication network110may utilize conventional transmission technologies including, for example, Ethernet and Wi-Fi to facilitate communications between the train cars. Each bogie diagnosis computer system may implement one or more transport layer protocols generally known in the art such as TCP and/or UDP. In some embodiments, the bogie diagnosis computer system includes functionality that allows the transport protocol to be selected based on real-time requirements or a guaranteed quality of service. For example, for near-real time communications UDP may be used by default, while TCP is used for communications which have more lax timing requirements but require additional reliability.

FIG.2illustrates an example Bogie Diagnostics Computer System200, according to some embodiments. This example includes two interfaces for receiving data from external systems. First, a Bogie Interface210is configured to facilitate communication with the bogie sensor network. In some embodiments, the bogie sensor network is directly connected to the Bogie Diagnostics Computer System200such that the task of the Bogie Interface210is primarily to encode and decode sensor data, as necessary, and perform any pre-processing that is required for processing the bogie sensor data. In other embodiments, one or more networks may be connected to the Bogie Diagnostics Computer System200with the bogie sensor network. For example, in some embodiments, the Bogie Diagnostics Computer System200and the bogie sensor network are connected through a wireless local area network. In this case, the Bogie Interface210will additionally include functionality for supporting the networking protocols used for communication. The Diagnostics Network Interface220is configured in a similar manner to the Bogie Interface210, except the former is used to connect to the network connecting the Bogie Diagnostics Computer System200with the other bogie diagnostics computer systems and other computing systems (e.g., a train control system) present on the train. As noted above with respect toFIG.1, a diagnostics network connects the various systems on the train. The Diagnostics Network Interface220implements the protocol(s) and performs any other tasks necessary to send and receive data on the network.

Continuing with reference toFIG.2, the Bogie Diagnostics Computer System200further includes one or more Processors205and a Program Storage215storing a plurality of software programs executable by the Processors205. The Program Storage215may be implemented using any non-transitory computer readable medium known in the art. The programs include an Anomaly Detection Program215A, a Diagnostics Program215B, and one or more Other Programs215C.

The Anomaly Detection Program215A is configured to detect track anomalies based on the sensor data collected by the Bogie Interface210. The Anomaly Detection Program215A may execute one or more algorithms that analyze data from the bogie sensor network and try to detect any irregularities, unexpected variances, or other anomalies in the data. If any anomalies are detected, the Anomaly Detection Program215A may use the Diagnostics Network Interface220to send an anomaly detection message to the other systems of the train (e.g., using a broadcast or multicast message).

Computationally, the processing resources of the Bogie Diagnostics Computer System200may not allow processing and storage of highly sampled data over extended periods of time. For this reason, the Anomaly Detection Program215A executed with a sampling rate parameter that allows the sampling of bogie sensor data to be increased or decreased, as desired. For example, if the Bogie Diagnostics Computer System200receives a notification that a potential anomaly is located at a particular location on the track, the sampling rate of the Anomaly Detection Program215A may be increased when the bogies associated with the Bogie Diagnostics Computer System200are passing over the location.

The Diagnostics Program215B performs general operations of the Bogie Diagnosis Computer System200and manages execution of the programs in the Program Storage215. For example, in one embodiment, the Diagnostics Program215B is configured to increase the sampling rate of the Anomaly Detection Program215A in response to receiving an anomaly detection message from at least one other bogie diagnostics computer system. Alternatively (or additionally), the Diagnostics Program215B may be configured to disable one or more of the Other Programs215C when anomaly detection message is received to allow the full processing resources of the Bogie Diagnosis Computer System200to be dedicated to anomaly detection.

FIG.3illustrates a method300of monitoring track condition, according to some embodiments. This method may be performed, for example, by one or more bogie diagnosis computer systems (seeFIG.2). Starting at step305, first sensor data corresponding to a track location is collected from a first sensor network on a first train car. In some embodiments, the track location is determined based on a Global Positioning System (GPS) signal received by the diagnostics system on the first train car. In other embodiments, the diagnostics system may receive readings of one or more location markings on the track (e.g., via the bogie sensor system). Then, the track location may be determined based on the location markings. For example, the rail system of the track may include a radio frequency identification device (RFID) tag or similar device that provides the latitude and longitude of a particular section of the track. As the bogie sensor system passes over the section, it receives the latitude and longitude from the RFID tag and uses it to update its internal positioning system. RFID tags may be distributed along the track system to provide location information at regular intervals and techniques such as dead reckoning which can be used to approximate position information between points.

Based on the first sensor data, at step310a potential track anomaly is identified at the track location by a first diagnostics system on the first train car (e.g., using the Anomaly Detection Program215A). At step315, a message describing the anomaly from the first diagnostics system is transmitted to diagnostics systems located on one or more other train cars included in the train. This message comprises an indication of the track location and, optionally, a description of the anomaly. In general, any technique known in the art may be used for passing messages between various components. For example, in some embodiments, the messages are designed to fit in a single IP packet to allow rapid communication of information between different computing systems. For example, in one embodiment, a notification message may comprise one or more fields describing the type of notification (e.g., new anomaly, confirmation of existing anomaly, etc.), while another field stores location information. In other embodiments, a file may be used to transfer message information using a format such as Extensible Markup Language (XML). This allows more detailed information to be sent with each transmission.

At step320, the message is received by a second diagnostics system on a second train car located behind the first train with respect to the train's direction of travel. In principle, trains ahead and behind the first train may receive the message. For example, in one embodiment, the notification message is transmitted using broadcast or multicast such that all computers connected to the diagnostics communication network can receive the message. However, the cars trailing the first car with respect to the train's direction of travel will have the opportunity to confirm the anomaly because the cars have not yet passed the anomaly on the track.

At step325, the second diagnostics system determines the time at which the second train car will be passing over track location. This time will depend on factors such as the speed of the train, the length of cars, the diameter of the wheels, etc. Because the design of each train may be different, each individual diagnostics system may be configured to calculate time differently. For example, upon linking up with a train, a diagnostics system may receive a car number indicating which car they are in the train system (e.g., “1” for the first car, “2” for the second car, etc.). Additionally, the diagnostics system may maintain information about the physical design of the bearings, shafts, brakes and wheels, as well as the overall length over the bogie. In some embodiments, this information may be updated over time, for example, as wheels shrink in diameter from use. To calculate speed a particular train may retrieve the current train speed from an external system (e.g., the train control system) or calculate it locally. Finally, with the car number, design information, and speed, location can be predicted. For example, the diagnostics system may predict that, given the current speed, the wheels of the car should pass over the location of the potential anomaly in exactly 10 seconds.

At step330, second sensor data is collected at the determined time and at the track location by the sensor network on the second train car. In some embodiments, prior to collecting the second sensor data and in response to receiving the message, the second diagnostics system may perform operations such as increasing sampling speed of the bogie sensor network on the second train car, enabling data collection algorithms that include functionality related to detection of the anomaly, or disabling data collection algorithms with functionality unrelated to detection of the anomaly. Examples of the type of functionality that may be enabled include reasoning logic (e.g., is the anomaly caused by a track issue or was it just a temporary issue like a stone on the track) and verification if car one had a faulty sensor read.

Then, at step335, if the track anomaly is present in both the first sensor data and the second sensor data at the track location, the train control system is notified of the track anomaly. Once the train control system receives this notification, it may perform various operations. For example, in some embodiments, the train control system sends an anomaly notification message to an external source such as the regional train management system. This anomaly notification message may provide information such as the location of the anomaly and the type of anomaly (if known). Additionally, configuration information such as the details of the system recording the sensor data, the number of diagnostic systems confirming the anomaly, etc. may also be included in the anomaly detection message. Alternatively (or additionally), the train control system may use the information to generate a map of the track as described below with respect toFIG.4.

In the systems described above, anomaly detection is performed cooperatively among cars of the train. This general framework can be scaled to perform anomaly detection across trains. For example, in one embodiment, the modified map of the track can be verified by other trains passing that location at a later time. The map can also be used by other trains to adjust their operating conditions (e.g., reduce speed if track failure).

FIG.4shows a method400for generating a map of a track using the anomaly detection system described herein. Starting at step405, the diagnostics system on a first train car collects sensor data from its local sensor network at a track location. At step410, a potential track anomaly at the track location is identified based on the collected sensor data. Next, at step415, the potential track anomaly is correlated by a second train car by collecting sensor data using its local sensor network at the track location. Once the anomaly is correlated, at step420it is used to update a map of the track to indicate a track anomaly at the track location. In general, any map file format known in the art may be used to encode the geographical information from the track into a computer file. For example, in one embodiment, the track information is encoded to a geographic information system (GIS) file format such Shapefile or Keyhole Markup Language (KML). The map may be generated locally or remotely from the train. In the example ofFIG.4, the map is generated by the train control system and, at step425, the map is relayed to an external system that is remote from the train. In other embodiments, the map is generated at the external system based on information provided by the train (e.g., anomalies and associated location information).

FIG.5illustrates an exemplary computing environment500within which embodiments of the invention may be implemented. For example, this computing environment500may be used to implement bogie diagnostics computer system described above with respect toFIGS.1and2. The computing environment500includes computer system510, which is one example of a computing system upon which embodiments of the invention may be implemented. Computers and computing environments, such as computer system510and computing environment500, are known to those of skill in the art and thus are described briefly here.

As shown inFIG.5, the computer system510may include a communication mechanism such as a bus521or other communication mechanism for communicating information within the computer system510. The computer system510further includes one or more processors520coupled with the bus521for processing the information. The processors520may include one or more central processing units (CPUs), graphical processing units (GPUs), or any other processor known in the art.

The computer system510also includes a system memory530coupled to the bus521for storing information and instructions to be executed by processors520. The system memory530may include computer readable storage media in the form of volatile and/or nonvolatile memory, such as read only memory (ROM)531and/or random access memory (RAM)532. The system memory RAM532may include other dynamic storage device(s) (e.g., dynamic RAM, static RAM, and synchronous DRAM). The system memory ROM531may include other static storage device(s) (e.g., programmable ROM, erasable PROM, and electrically erasable PROM). In addition, the system memory530may be used for storing temporary variables or other intermediate information during the execution of instructions by the processors520. A basic input/output system533(BIOS) containing the basic routines that help to transfer information between elements within computer system510, such as during start-up, may be stored in ROM531. RAM532may contain data and/or program modules that are immediately accessible to and/or presently being operated on by the processors520. System memory530may additionally include, for example, operating system534, application programs535, other program modules536and program data537.

The computer system510also includes a disk controller540coupled to the bus521to control one or more storage devices for storing information and instructions, such as a hard disk541and a removable media drive542(e.g., floppy disk drive, compact disc drive, tape drive, and/or solid state drive). The storage devices may be added to the computer system510using an appropriate device interface (e.g., a small computer system interface (SCSI), integrated device electronics (IDE), Universal Serial Bus (USB), or FireWire).

The computer system510may also include a display controller565coupled to the bus521to control a display566, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a computer user. The computer system includes an input interface560and one or more input devices, such as a keyboard562and a pointing device561, for interacting with a computer user and providing information to the processor520. The pointing device561, for example, may be a mouse, a trackball, or a pointing stick for communicating direction information and command selections to the processor520and for controlling cursor movement on the display566. The display566may provide a touch screen interface which allows input to supplement or replace the communication of direction information and command selections by the pointing device561.

The computer system510may perform a portion or all of the processing steps of embodiments of the invention in response to the processors520executing one or more sequences of one or more instructions contained in a memory, such as the system memory530. Such instructions may be read into the system memory530from another computer readable medium, such as a hard disk541or a removable media drive542. The hard disk541may contain one or more datastores and data files used by embodiments of the present invention. Datastore contents and data files may be encrypted to improve security. The processors520may also be employed in a multi-processing arrangement to execute the one or more sequences of instructions contained in system memory530. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and software.

The computing environment500may further include the computer system510operating in a networked environment using logical connections to one or more remote computers, such as remote computer580. Remote computer580may be a personal computer (laptop or desktop), a mobile device, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to computer system510. When used in a networking environment, computer system510may include modem572for establishing communications over a network571, such as the Internet. Modem572may be connected to bus521via user network interface570, or via another appropriate mechanism.

The embodiments of the present disclosure may be implemented with any combination of hardware and software. In addition, the embodiments of the present disclosure may be included in an article of manufacture (e.g., one or more computer program products) having, for example, computer-readable, non-transitory media. The media has embodied therein, for instance, computer readable program code for providing and facilitating the mechanisms of the embodiments of the present disclosure. The article of manufacture can be included as part of a computer system or sold separately.

A graphical user interface (GUI), as used herein, comprises one or more display images, generated by a display processor and enabling user interaction with a processor or other device and associated data acquisition and processing functions. The GUI also includes an executable procedure or executable application. The executable procedure or executable application conditions the display processor to generate signals representing the GUI display images. These signals are supplied to a display device which displays the image for viewing by the user. The processor, under control of an executable procedure or executable application, manipulates the GUI display images in response to signals received from the input devices. In this way, the user may interact with the display image using the input devices, enabling user interaction with the processor or other device.

The functions and process steps herein may be performed automatically or wholly or partially in response to user command. An activity (including a step) performed automatically is performed in response to one or more executable instructions or device operation without user direct initiation of the activity.