System and method for identifying candidate vehicle system

Abstract

To provide a system including a controller with at least one processor.SOLUTION: At least one processor performs the steps of: acquiring first vehicle system data from a first vehicle system 302 of a plurality of vehicle systems 302 on the basis of common characteristics shared by the plurality of vehicle systems 302; acquiring second vehicle system data from a second vehicle system 302, the second vehicle system data being based on common characteristics shared by at least two vehicle systems 302; comparing the first vehicle system data with the second vehicle system data; and identifying one of the first vehicle system 302 and the second vehicle system 302 as a candidate vehicle system for maintenance on the basis of the comparison of the first vehicle system data with the second vehicle system data.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The subject matter described herein relates to monitoring and comparing vehicle system data from multiple vehicle systems to identify candidate vehicle systems for repair and maintenance. [Background technology]

[0002] Vehicle systems are found in many different environments and settings, from fleets of cars and / or trucks making deliveries using highways and roads, to rail vehicle systems traveling on railroad tracks, to fleets of airplanes traveling through the air, to fleets of ships traveling through the water, each vehicle system being a single vehicle or multiple interconnected vehicles traveling along such routes, airways, waterways, etc.

[0003] Vehicle system data is continually acquired as vehicle systems improve communications, safety, and the like. Vehicle system data can include location data, data acquired by sensors monitoring the operating system or components of the operating system, and the like. As vehicle system data is acquired, analytics are used to improve the operation of the vehicle system. Whether making decisions related to the best route to take or identifying when maintenance is needed, algorithms, including artificial intelligence algorithms, are a popular modality for providing such improvements.

[0004] The use of algorithms, particularly artificial intelligence algorithms, can still have drawbacks. In particular, a significant amount of memory space, processing resources, etc., is typically required to utilize the algorithm. Additionally, often the algorithm simply does not consider all of the different variables that a vehicle system may encounter. Weather, humidity, precipitation, terrain, vehicle system age, vehicle system wear, wind conditions, etc., can all affect the performance of the vehicle system's operational system. As a result, algorithms that do not properly consider all of these variables may make decisions related to maintenance or repair schedules when maintenance or repair is not required. Additionally, these algorithms may miss cases where the vehicle system needs maintenance or repair, resulting in greater damage caused as a result of operating with a malfunctioning operational system. Summary of the Invention

[0005] According to one embodiment, a system is provided that includes a controller having one or more processors. The one or more processors may be configured to: acquire first vehicle system data from a first vehicle system of the plurality of vehicle systems based on a common characteristic shared by the plurality of vehicle systems; and acquire second vehicle system data from a second vehicle system of the plurality of vehicle systems, the second vehicle system data being based on the common characteristic shared by the two or more vehicle systems. The one or more processors may also be configured to compare the first vehicle system data with the second vehicle system data and identify one of the first vehicle system or the second vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the second vehicle system data.

[0006] According to one embodiment, a system may include a controller having one or more processors. The one or more processors may be configured to acquire first vehicle system data from a first vehicle system in a determined area and acquire additional vehicle system data from a plurality of additional vehicle systems in the determined area. The one or more processors may also be configured to compare the first vehicle system data with the additional vehicle system data and identify the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the additional vehicle system data.

[0007] According to one embodiment, a method may be provided that includes searching for and identifying vehicle systems based on a common characteristic and determining whether a threshold number of vehicle systems have been identified during the search. The method may also include varying the common characteristic in response to the threshold number of vehicle systems not being identified and performing an additional search after varying the common characteristic. The method may also include acquiring first vehicle system data associated with a first operating system from a first vehicle system identified in the additional search, acquiring additional vehicle system data associated with additional operating systems of a plurality of additional vehicle systems identified in the additional search, the first operating system being associated with the additional operating systems, and identifying the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the additional vehicle system data. [Brief explanation of the drawings]

[0008] The subject matter of the present invention can be understood from reading the following description of non-limiting embodiments with reference to the accompanying drawings, in which:

[0009] [Figure 1] FIG. 1 is a schematic diagram of a vehicle system. [Figure 2] FIG. 2 is a schematic diagram of a control system for the vehicle system. [Figure 3]1 is a schematic diagram of the environment of a vehicle system. [Figure 4] FIG. 1 is a block flow diagram of a method for identifying a malfunctioning operating system of a vehicle system. [Figure 5A] 1 is a graph of vehicle system data. [Figure 5B] 1 is a graph of vehicle system data. [Figure 6A] 1 is a graph of vehicle system data. [Figure 6B] 1 is a graph of vehicle system data. DETAILED DESCRIPTION OF THE INVENTION

[0010] One or more embodiments of the subject matter described herein relate to a vehicle system control system that searches for and identifies common characteristics among different and / or separate vehicle systems. The system then obtains vehicle system data from each vehicle system identified based on the shared common characteristics. The vehicle system data may be related to an operational system of each vehicle system. The vehicle system data related to each vehicle's operational system is then compared with vehicle system data of other vehicle systems to identify anomalies in the vehicle system data of one or more individual vehicle systems. If a vehicle system data anomaly exists for a particular vehicle system, that vehicle system is identified as a candidate vehicle system for repair or maintenance. The identification may be performed during a trip such that communication can be provided to a remote controller, such as a maintenance controller, to schedule maintenance and / or repair of the candidate vehicle system.

[0011] FIG. 1 illustrates a schematic diagram of one embodiment of a vehicle system 100. While FIG. 1 illustrates the vehicle system as a rail vehicle, in other embodiments, the vehicle system may include an automobile, a watercraft, an aircraft, an off-road vehicle, a construction vehicle, a fleet vehicle, etc. In particular, the vehicle system may include a single vehicle or two or more vehicles. The vehicle system may be configured to travel along a route 104 from a departure or starting location to a destination or arrival location. In the example, the vehicle system includes a propulsion generating vehicle 108 and a non-propulsion generating vehicle 110 mechanically interconnected to each other for traveling in unison along the route. The vehicle system may include at least one propulsion generating vehicle and, optionally, one or more non-propulsion generating vehicles. Alternatively, the vehicle system may be formed from only a single propulsion generating vehicle.

[0012] A propulsion-generating vehicle may generate traction to propel (e.g., pull or push) the vehicle system along a route. The propulsion-generating vehicle includes a propulsion system, such as an engine, one or more traction motors, etc., that operates to generate traction to propel the vehicle system. While FIG. 1 illustrates one propulsion-generating vehicle and one non-propulsion-generating vehicle, the vehicle system may include multiple propulsion-generating vehicles and / or multiple non-propulsion-generating vehicles. In alternative embodiments, the vehicle system includes only propulsion vehicles, such that the propulsion-generating vehicles are not coupled to non-propulsion-generating vehicles or other types of vehicles. In yet other embodiments, the vehicles of a vehicle system are logically or virtually coupled to each other but are not mechanically coupled to each other. For example, the vehicles may communicate with each other to coordinate their movement such that the vehicles move in unison as a convoy (e.g., a vehicle system) without being coupled to each other by a coupler.

[0013] The propulsion generating vehicle also includes one or more other motion systems 112 that control the operation of the vehicle systems. In one embodiment, the motion system is a braking system that generates braking forces to slow or stop the movement of the vehicle system. Alternatively, the motion system may be a heating and cooling system, an engine and / or power transmission system, a bearing system, a wheel system, or other mechanical, electromechanical, or electrical system used during or for the operation of the vehicle system.

[0014] In the example of FIG. 1 , the vehicles of the vehicle system each include a plurality of path-engaging wheels 120 and at least one axle 122 interconnecting the left and right wheels (only the left wheel is shown in FIG. 1 ). Optionally, the wheels and axles are located on one or more trucks or bogies 118. Optionally, the trucks may be fixed-axle trucks, such that the wheels are rotationally fixed to the axles, and thus the left wheel rotates at the same speed, amount, and simultaneously as the right wheel. In one embodiment, the vehicle system may not include axles, such as some mining vehicles, electric vehicles, etc.

[0015] The vehicle system may also include a vehicle controller 124 (e.g., 214, FIG. 2 ), which may further include a wireless communication system 126 that enables wireless communication between vehicles in the vehicle system and / or with a remote location, such as a remote controller 128 at a remote (e.g., dispatch) location. The communication system may include a receiver and a transmitter, or a transceiver that performs both receiving and transmitting functions. The communication system may also include an antenna and associated circuitry.

[0016] The vehicle system may also include a locator device 136. The locator device may be located on the vehicle system, may utilize roadside equipment, or the like. In one example, the locator device is a Global Navigation Satellite System (GNSS) receiver, such as a Global Positioning System (GPS) receiver, that can receive signals from remote sources (e.g., satellites) for use in determining the vehicle system's position, movement, course, speed, etc., and provide location data related to the vehicle system. Alternatively, the locator device may provide location information using WiFi, Bluetooth-enabled beacons, near field communications (NFC), radio frequency identification (RFID), QR codes, etc.

[0017] FIG. 2 provides a schematic diagram of a control system 200 that may be configured to communicate with and monitor multiple vehicle systems. To this end, vehicle systems may include automobiles, rail vehicles, ships, airplanes, off-road vehicles, construction vehicles, fleet vehicles, etc. The control system includes a supervisory controller 201 that includes one or more processors 202 (e.g., microprocessors, integrated circuits, field programmable gate arrays, etc.). The supervisory controller may be located remotely from the vehicle systems, such as at a dispatch, station, or stationary location. The one or more processors may receive location data from the vehicle controller, operational data from operational systems, etc. Based on receiving data related to vehicle system data associated with other vehicle systems traveling within the determined or defined area, the one or more processors make determinations related to the health of the monitored vehicle systems to identify one or more candidate vehicle systems for maintenance or repair. The determined area may be a geographic area that may be automatically or manually defined. As an example, a circle having a radius of five miles from the determined location may be the determined area. An area where a particular weather event, such as rain, is occurring may be the determined area. In one embodiment, a determined region may have one or more boundaries that are fixed and do not change. Alternatively, one or more boundaries of a region may change. For example, a region may include a location where precipitation is occurring. Optionally, a region may be defined by a zip code, city boundaries, county boundaries, state boundaries, etc. In this manner, a first determined region may be provided, and then a second, larger or smaller determined region may be provided. Furthermore, the location of the region, or the perimeter of the determined region, may change. In an embodiment, the region may be equal, but the perimeter may move, resulting in a first determined region (e.g., original perimeter) and a second determined region (e.g., moved perimeter).

[0018] The supervisory controller may also optionally include memory 204, which may be an electronic computer-readable storage device or medium. The supervisory controller memory may be within the supervisory controller's housing or, alternatively, on a separate device that may be communicatively coupled to the controller and one or more processors within the controller. "Communicatively coupled" means that two devices, systems, subsystems, assemblies, modules, components, etc. are connected by one or more wired or wireless communication links, such as one or more conductive (e.g., copper) wires, cables, or buses; a wireless network; or a fiber optic cable. The controller memory may include a tangible, non-transitory computer-readable storage medium that temporarily or permanently stores data for use by the one or more processors. The memory may include one or more volatile and / or non-volatile memory devices, such as random access memory (RAM), static random access memory (SRAM), dynamic RAM (DRAM), another type of RAM, read-only memory (ROM), flash memory, magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tape), optical disks, etc. The memory may be utilized to store information related to location data, movement data, history data, route data, vehicle data, etc. The memory may then be used by one or more processors to access the data for making determinations related to the health of each vehicle system, including the health of each operational system of each vehicle system. In one embodiment, the data is logged in a document associated with the vehicle system. In another embodiment, data such as a video feed may be recorded and stored in memory for later analysis. Additionally, algorithms, applications, models, etc. may also be stored in the memory for use by one or more processors in making determinations related to the health of vehicle systems in a region.

[0019] The supervisory controller may also include a transceiver 206 configured to communicate with multiple vehicle controllers. The transceiver may be a single unit or may be a separate receiver and transmitter. In one embodiment, the transceiver may only transmit signals, but may alternatively emit (e.g., transmit and / or broadcast) and receive signals.

[0020] The supervisory controller may also include input devices 208 and output devices 210. An input device may be an interface between an operator or supervisor and one or more processors. An input device may include a display or touch screen, input buttons, a port for accepting a memory device, etc. In this manner, an operator or supervisor may manually provide parameters, including vehicle parameters, route parameters, and journey parameters, to the controller. Similarly, an output device may present information and data to an operator or provide prompts for information and data. An output device may also be a display or touch screen. In this manner, a display or touch screen may be an input device and an output device.

[0021] The supervisory controller may additionally include a prescription application or system 212 for determining the health of vehicle systems in communication with the supervisory controller. The prescription application may be a program, instructions, etc. that may be utilized by one or more processors to search for and make identifications, determinations, etc. related to the health of a plurality of vehicle systems. Optionally, the prescription application may include and / or represent hardware circuitry coupled to one or more processors for performing the operations described in connection with the prescription system. After the prescription application identifies candidate vehicle systems, a prescription, or suggested testing, repair, maintenance, etc., may be communicated to a remote controller for maintenance and repair of the vehicle systems.

[0022] The supervisory controller receives data from the vehicle controllers 214 of the vehicle systems, compares and analyzes the data, and performs health diagnostics related to individual vehicle systems. In one embodiment, only those vehicle controllers on vehicle systems within a defined region transmit their vehicle system data to the supervisory controller. Alternatively, one or more other vehicle controllers on vehicle systems not within the region can transmit their vehicle system data to the supervisory controller. While FIG. 2 illustrates two vehicle controllers, in other examples, five vehicle controllers, ten vehicle controllers, one hundred vehicle controllers, etc. may provide data to the supervisory controller. In one example, the prescription application may reduce the number of common characteristics (e.g., variables) that may cause degradation in vehicle system performance to increase the number of vehicle systems identified for comparison and analysis. Alternatively, the prescription application may increase the number of common characteristics that may cause degradation in vehicle system performance to decrease the number of vehicle systems identified for comparison and analysis.

[0023] In an embodiment, the variables are weather and environmental conditions in a defined geographic region. In particular, the operation of vehicle systems can be significantly affected by weather. For example, wheel sensors may monitor the wheel speed of a rail vehicle to determine wheel slip. As wheels become worn or uneven, they may become more prone to slip on the track, causing wheel sensors to measure wheel rotational speed versus expected rotational speed to capture when wheel slip occurs in an attempt to diagnose a defective tire. However, environmental conditions including rain, snow, humidity, ice, wind, rail gradient, etc. can also cause wheel slip. As a result, when an algorithm, such as an artificial intelligence (AI) algorithm, having a threshold number of wheel slips to diagnose a defective wheel is utilized, errors can occur correspondingly because there is no way to consider additional wheel slip that occurs as a result of weather instead of wear. Therefore, a prescription application can utilize common characteristics of weather to provide improved determinations.

[0024] In one example, the common characteristic may simply be obtained by obtaining data from vehicle systems in a determined region and then comparing the vehicle system data of such vehicle systems with each other. In one embodiment, the determined region may be a distance from a geographic location. In one example, the determined region may be a one-mile radius, and in another example, the determined region may be a two-mile radius, a ten-mile radius, etc. In yet another example, the prescription application may receive local weather radar to determine a region where a determined weather event, such as rain, is occurring and place the determined region within the region where the rain is present. To this end, the prescription application may also identify similar weather events in different locations. Thus, if a vehicle system in Florida is traveling in rainy and 20°C weather and a vehicle system in Virginia is also traveling in rainy and 20°C weather, the vehicle systems share a common characteristic even though they are in different geographic locations. In yet another example, the prescription application may have an initial determined region, such as a one-mile radius around the determined location, and if a threshold number of vehicle systems are not located in the determined region, the determined region may be increased to a later determined region, such as a two-mile radius around the determined location. The determined region may then continue to grow until a threshold number of vehicle systems in the region is reached.

[0025] In this example, as the prescription application receives vehicle system data from vehicle controllers in a defined region, it compares the vehicle system data (e.g., wheel slip data) of each vehicle system with other vehicle systems to identify anomalies, e.g., indications of unhealthy wheels. In one example, a specified deviation threshold may be utilized for the analysis and comparison. As a function of the vehicle system data in question and common characteristics, the deviation threshold is a specified delta or difference between two or more data sets (data points or groups of data) that indicates that one of the data sets is sufficiently different from the other to reflect an increased or greater likelihood of the underlying / related vehicle system needing maintenance. Thus, if one data set (associated with one vehicle system) is within a specified deviation threshold of other data (of the other vehicle system), this may not indicate a greater likelihood of needed maintenance, whereas if one data set is outside the deviation threshold of the other data, this may indicate a greater likelihood of needed maintenance. For example, the specified deviation threshold may be a standard deviation threshold. The standard deviation is the average distance from the mean of a group. In one example, the standard deviation threshold is the standard deviation itself. In this manner, if 100 vehicle systems provide wheel slip data for a defined region and the average number of wheel slips while traveling through the defined region is 15 with a standard deviation of 3 wheel slips, the standard deviation threshold is 18 wheel slips. As a result, any vehicle system that experiences more than 18 wheel slips while in the defined region may be a candidate vehicle system for maintenance. Alternatively, the specified deviation threshold may represent the standard deviation plus a determined amount. Thus, in the previous example, two additional wheel slips may be added to the calculated standard deviation so that the specified deviation threshold is 20 wheel slips. Thus, any vehicle system that records more than 20 wheel slips while in the defined region may be a candidate vehicle system for maintenance.Time and / or continuity may also be considered, for example, the number of wheel slips during a specified period of time or during specified consecutive periods of time while in a defined area.

[0026] In an exemplary embodiment, calculations for determining and identifying candidate vehicle systems may be performed using an average, standard deviation, or the like, although other calculations may be performed based on a specified deviation threshold or otherwise. For example, in this example, if 100 vehicle systems in a defined region are analyzed, a mode associated with the number of wheel slips may be utilized. In this example, the mode number of wheel slips for the 100 vehicle systems may be 14 wheel slips. A quantity determined from the mode, such as five (5) wheel slips, may then be provided to determine a threshold number of wheel slips. As a result, any vehicle systems of the 100 vehicle systems in the defined region that have more than 19 (19) wheel slips are determined and identified as candidate vehicle systems for maintenance.

[0027] Additionally, while in one embodiment, the variable eliminated by utilizing the common characteristic is the environment, in another embodiment, the common characteristic may be engine type, engine manufacturer, vehicle system age, vehicle system mileage, geographic location on the route, such as a particular tunnel, bridge, straightaway, route section with a similar elevation, gradient, etc. In another embodiment, a determined region may not be utilized, and instead, historical data for a particular engine type may be utilized for comparison. In yet another embodiment, vehicle system age may be utilized as the common characteristic, such that data is retrieved only for vehicle systems within a determined age range, such as airplanes that are 5 to 10 years old. In another embodiment, the common characteristic may be the amount of mileage the vehicle system has. For example, a prescription application may retrieve only vehicle system data associated with cars with 100,000 to 150,000 miles to compare performance.

[0028] Additionally, multiple common characteristics may be utilized. For example, vehicle system data may be obtained from a determined region for a particular engine type. In one embodiment, vehicle system data related to the determined region may have a first weight associated therewith, while vehicle system data related to a particular engine type may have a second weight associated therewith. In examples, the weights may be the same, different, or variable based on the use of algorithms, including artificial intelligence algorithms, etc. For example, a prescription application may obtain automobile vehicle system data for all vehicle systems of a particular manufacturer within a five-mile radius that are less than five years old. Thus, by taking similar vehicle systems and comparing the vehicle system data of such similar vehicle systems, differences or deviations (e.g., anomalies) that may indicate an unhealthy condition of the vehicle system's operating system can be determined to identify candidate vehicle systems for repair and maintenance.

[0029] In one embodiment, the comparison of the vehicle system data may be a comparison of the first vehicle system data with the second vehicle system data. The comparison may also include a comparison of the first vehicle system data with additional vehicle system data. To this end, the second vehicle system data may be compared with the additional vehicle system data.

[0030] Each vehicle controller may include one or more processors 218 (such as a microprocessor, integrated circuit, field programmable gate array, etc.), memory 220, which may be an electronic computer-readable storage device or medium, a transceiver 222 configured to communicate with the supervisory controller, input devices 224, and output devices 226. The input devices may be an interface between an operator or supervisor and the one or more processors. The input devices may include a display or touch screen, input buttons, a port for accepting a memory device, etc. In this manner, the operator or supervisor may manually provide parameters, including vehicle parameters, route parameters, and journey parameters, to the vehicle controller.

[0031] The controller may also include one or more sensors 228 disposed within and adjacent to the area to detect movement data, area data, vehicle data, route data, etc. The one or more sensors may be pressure sensors, temperature sensors, speed sensors, voltmeters, angular velocity sensors, etc., and may measure fluid levels, wheel speeds, axle temperatures, fluid temperatures, engine performance, brake performance, wear, etc. The one or more sensors monitor different operating systems of the vehicle system to obtain and analyze vehicle system data that may be utilized by a prescription application or by one or more processors of the vehicle controller to make decisions that are communicated to the prescription application. The vehicle system data from each vehicle system may then be compared with each other to determine faulty and unhealthy operating systems. Optionally, the vehicle controller may also include a prescription application 230 to more efficiently process data and information for communication with the prescription application of the monitoring device.

[0032] In one example, the one or more sensors may include a locator device. In one example, the locator device is a GNSS receiver, such as a Global Positioning System (GPS) receiver, that can receive signals from remote sources (e.g., satellites) for use in determining the vehicle's position, movement, course, speed, etc., and provide location data related to the vehicle system. Alternatively, the locator device may provide location information using WiFi, Bluetooth-enabled beacons, near field communications (NFC), radio frequency identification (RFID), QR codes, etc.

[0033] FIG. 3 illustrates an example environment 300 in which one or more vehicle systems 302 are monitored to identify one or more candidate vehicle systems for repair or maintenance as a result of a malfunctioning operating system. The environment may include roads, railroads, waterways, runways, airways, etc. For purposes of this discussion, FIG. 3 illustrates the vehicle system as an automobile, but the vehicle system may also be a rail vehicle, a watercraft, an airplane, an off-road vehicle, a construction vehicle, a fleet vehicle, etc. In particular, the vehicle system may include a single vehicle, as provided in FIG. 3, or alternatively, may include multiple interconnected vehicles. In one embodiment, the vehicle system is a rail vehicle, as illustrated in FIG. 1.

[0034] Each vehicle system may include a vehicle controller (FIG. 2) with a vehicle locator device. Each vehicle controller may communicate with a supervisory controller that includes a prescription application. The supervisory controller may be located remotely from the vehicle system and may be a dispatch controller, a station controller, an air traffic control tower controller, etc.

[0035] In one embodiment, the prescription application may continuously receive positional and operational data from each of the vehicle systems within the determined region 304. In the example of FIG. 3, a first determined region 304A and a second determined region 304B are provided. Notably, in one embodiment, the prescription application receives vehicle system data only from vehicle systems within the first determined region; however, the prescription application may determine that a threshold number of vehicle systems are not located within the first determined region, and utilize a larger second determined region for receiving operational data. After receiving the vehicle system data, the prescription application may compare the vehicle system data of the vehicle systems to determine anomalies. For example, the received vehicle system data may be the temperature of the lubricant in the axle gearbox. Each temperature may then be compared, averaged, a mode determined, a standard deviation determined, etc., to determine whether an anomaly exists in one of the four vehicles. Alternatively, engine temperature, wheel slip, wheel angular velocity, wheel temperature, brake pressure, etc. may all be obtained for comparison to determine which operational systems may be malfunctioning. In this way, candidate vehicle systems for repair, maintenance, etc. can be identified while the vehicle system is in operation. Since only the determined regions are utilized as common characteristics, variations resulting from the environment of outside temperature differences are eliminated, improving the accuracy of diagnosis.

[0036] In this example, the determined area is used as a common characteristic to determine which vehicle systems will be compared to each other, although in other examples, other common characteristics may be used. For example, the prescription application may use all vehicle systems with the same or similar engine type or model, vehicle systems of similar age or mileage, vehicle systems taking similar or the same route, combinations thereof, etc. In one example, vehicle system data may be obtained from similar geographic locations on the route, such as a particular tunnel, bridge, straight stretch, a section of route with a similar elevation, gradient, etc. In this way, vehicle system data from vehicle systems in similar situations may be compared, accounting for variations as a result of malfunctioning components of the operating systems, rather than results related to the environment, age, wear, etc.

[0037] FIG. 4 illustrates a method for identifying candidate vehicle systems for repair and / or maintenance. Candidate vehicle systems may require repair and / or maintenance as a result of an operating system or component of an operating system that is not operating, or an operating system or component that is operating but not operating as efficiently, as desired, etc. as other similarly situated operating systems or components. In one example, a wheel may be detected as slipping once every five miles, while other wheels of the vehicle system only slip once every 20 miles. In another example, the engine temperature of one vehicle system may operate 10° C. higher than another vehicle system engine. In this manner, the vehicle system may still continue to operate, but a higher frequency of wheel slip, temperature difference, etc. may indicate that it is not operating as efficiently, as desired, etc. as other operating systems. By identifying candidate vehicle systems while the vehicle system is on a route, maintenance can be scheduled to address the operating system before a more serious condition, such as a wheel failure, engine failure, etc., occurs.

[0038] In one embodiment, the vehicle system of Figure 1 is the vehicle system monitored for the method. In another embodiment, the control system of Figure 2 is utilized to implement the method of Figure 4. Similarly, in one embodiment, the environment and vehicle system of Figure 3 can be the environment and vehicle system that implements the method of Figure 4.

[0039] At 402, a determination is made whether the two or more vehicle systems share a common characteristic. The common characteristic may be any parameter, attribute, etc. shared by two or more vehicle systems. In one example, the common characteristic is a defined area. Thus, if the determined area is a 100-mile radius of the determined location, each vehicle system within the defined area shares the common characteristic of being within the defined area. In another example, the common characteristic may be vehicle system mileage. In this example, all vehicle systems with more than 100,000 miles may share the common characteristic of being more than 100,000 miles. In one example, the common characteristic may relate to the make and / or model of the vehicle, the make or model of the engine, the vehicle manufacturer, the make or type of tires, the outdoor temperature at which the vehicle system is operating, the outdoor weather conditions in which the vehicle is operating, including the presence of rain, sleet, snow, ice, wind, humidity, etc., the type of material utilized by the components of the operating system, such as tires, etc. In one example, the determination of the common characteristic may be provided by a user of the vehicle system, a user of a monitoring system monitoring multiple vehicle systems, set by a prescription application, determined by a prescription application, etc.

[0040] At 404, the vehicle systems are monitored, and vehicle system data related to operational systems and operational system components is communicated to a supervisory controller based on a common characteristic. For example, if the common characteristic is a defined area, then every vehicle system in the defined area communicates vehicle system data to the supervisory controller. Alternatively, if the vehicle system is an airplane, and the common characteristic is flying over an ocean on route, then every monitored vehicle system flying over an ocean during that route communicates vehicle system data to the supervisory controller. In each instance, because each vehicle system shares the common characteristic, when vehicle system data for one of the vehicle systems is compared to vehicle system data for another vehicle system, there is an increased likelihood that differences in the vehicle system data will be related to a malfunctioning or non-operating operational system, operational system component, sensor, etc.

[0041] At 406, a determination is optionally made as to whether additional vehicle system data is desired. In particular, the prescription application may include a threshold number of vehicle systems that must share common characteristics before a comparison can be made to identify candidate vehicle systems requiring repair and / or maintenance. In one example, the first defined area may be a 10-mile radius, but only three vehicle systems are detected at that radius. Because a threshold number of five vehicle systems is required for comparison, the first defined area may be increased to a second defined area, such as a 20-mile radius, at which seven vehicle systems are detected. Alternatively, instead of increasing the first defined area to a second defined area, historical data may be utilized to increase the number of vehicle systems for comparison. In particular, a reason for utilizing a defined area is to ensure that environmental and weather conditions do not introduce variability into the operational data. Thus, in one example, historical data from the defined area may be analyzed to determine similar weather conditions when the historical data was transmitted. In one embodiment, if only four vehicle systems are detected in the defined area because the weather conditions are rainy, historical data from vehicle systems acquired when rain was occurring is utilized. Thus, the database formed by the supervisory controller can be utilized with vehicle system data for additional vehicle systems to make decisions related to operating systems and components of operating systems.

[0042] In another example, a threshold can be used to increase the number of common characteristics between vehicle systems. For example, if a defined area has a 50-mile radius and 100 vehicles are detected, the prescription application can include a threshold number of 40 vehicles. As a result, once 100 vehicles are detected in the defined area, the prescription application can vary the common characteristic to be any vehicle system within the 50-mile radius that has a hybrid engine. As a result, the number of vehicle systems having the common characteristic drops to 8, preventing the threshold from being exceeded. In this manner, the common characteristic can be varied. Thus, when vehicle system data between vehicle systems is compared, faulty operation is the most likely cause of variance in the vehicle system data.

[0043] If additional vehicle system data is desired at 406, the vehicle system data continues to be communicated at 404. Thus, whether more vehicle system data, less vehicle system data, etc. is desired, the common characteristics can be varied to provide an improved data set for comparison.

[0044] If additional vehicle system data is not desired at 406, a comparison is made at 408 between the vehicle system data of at least the first vehicle system and the vehicle system data of the second vehicle system to identify a malfunctioning operating system or component of the operating system. In one example, the comparison includes determining whether data associated with one vehicle system is within a specified deviation threshold of corresponding data associated with multiple other vehicle systems; if it is within the threshold, the vehicle system is unlikely to be a candidate for maintenance; if it is outside the threshold, the vehicle system is likely to be a candidate for maintenance. In another example, the comparison is made by averaging measurements from each monitored vehicle system and determining whether the measurement is greater than a threshold percentage from the average. In another example, the comparison is made by providing a determined error factor from the average. Thus, if the average temperature is measured at 100°C, the determined error factor may be 5°C, such that any measurement at plus or minus 5°C is identified as a candidate vehicle system for maintenance. In alternative embodiments, the mode, mean, standard deviation, etc. may be used to provide the comparison and identify candidate vehicle systems. As a result, candidate vehicle systems for maintenance are identified based on identifying anomalies in the vehicle system data. By utilizing vehicle systems that are in the same defined area, have the same or similar environment, have the same or similar age, have the same or similar mileage, have the same make, engine model, or type, etc., more accurate comparisons can be made between vehicles to identify candidate vehicle systems. To this end, errors that may occur when vehicle system data is analyzed by an algorithm, artificial intelligence algorithm, or the like because certain variables are not taken into account can be reduced.

[0045] At 410, a determination is made whether the vehicle system has a malfunctioning operating system or operating system component based on a comparison of the first vehicle system data and the second vehicle system data. If it is determined that a malfunction is unlikely, the monitoring system continues to monitor vehicle systems having common characteristics. If a determination is made at 410 that a malfunctioning operating system or operating system component may be present, at 412, the vehicle controller communicates the first vehicle system data to a remote controller in response to identifying the first vehicle system as a candidate vehicle system. This communication may include the malfunctioning operating system or operating system component, a request to schedule maintenance or repair for the component or operating system, vehicle system data resulting in the determination, etc. In this way, maintenance can be scheduled as early as possible, preventing the malfunctioning system from causing significant damage to the vehicle system. Additionally, preparation for repair and maintenance can begin even before the vehicle system arrives at the maintenance location, improving the efficiency of maintenance at the maintenance location.

[0046] 5A and 5B illustrate graphs of vehicle system data in accordance with the systems and methods described herein. Graph 5A illustrates, on the X-axis, vehicle systems 502 that share a common characteristic. The common characteristic can be any of the common characteristics described above, including a determined distance from a geographic location (e.g., a determined region). Meanwhile, the Y-axis illustrates an operational system parameter, in this example, turbine temperature 504 for each of the vehicle systems. In one example, a temperature sensor is associated with the turbine of each vehicle system that transmits the turbine temperature. Each vehicle system has a corresponding turbine temperature 506, where an error factor, or variability, is also provided. From the graph, an anomaly 508 is provided for the vehicle system identified as 2906.

[0047] 5B, on the other hand, has the X-axis providing the exact same vehicle system 502, while the Y-axis provides the water-oil difference 510. Also, the corresponding water-oil difference 512 for each vehicle, which also includes variation or error. In this example, anomalies 514 are also provided in the vehicle system data for the vehicle system identified as 2906. Based on this comparison information, it can be determined that the vehicle system identified as 2906 is a candidate vehicle system requiring maintenance or repair. Thus, while the vehicle system is still on the route, a communication can be provided to a dispatch controller, maintenance controller, station controller, other remote controller, etc., providing the vehicle system data and scheduling maintenance for the vehicle system identified as 2906.

[0048] FIGS. 6A and 6B illustrate yet another example of vehicle system data that may be obtained and compared consistently with the methods and systems described herein. In this example, the X-axis again presents individual vehicle systems 602, while the Y-axis of FIG. 6A provides parameters, particularly manifold air temperature 604, against which each vehicle system's manifold air temperature 606 is compared. Again, reading errors and variations may be accounted for in an attempt to identify anomalies 608, which in this example is a vehicle system identified as vehicle system 8390. Meanwhile, FIG. 6B illustrates the same group of vehicle systems with an additional parameter, this time turbo inlet temperature 610, considered. Thus, each plot provides individual turbo inlet temperatures 612 for each vehicle system, and anomalies 614 are also illustrated for the vehicle system identified as vehicle system 8390. Thus, communications related to maintenance of vehicle system 8390 as a candidate vehicle system may occur. While in each example, anomalies are illustrated in both graphs for the same vehicle system, in other examples, only one graph may provide anomalies. Communications can then share this information to aid in diagnosing the component or operating system causing the malfunction.

[0049] Thus, a method and system for identifying candidate vehicle systems for maintenance and repair is provided that avoids the use of complex algorithms, including artificial intelligence algorithms, that occupy memory and processing space in control systems. Additionally, by utilizing vehicle systems that have common characteristics, candidate vehicle systems may be identified, thereby improving efficiency while also providing improved diagnostics.

[0050] In particular, the system identifies anomalies in data streams without prior training (e.g., using artificial intelligence) by measuring the difficulty of finding similarities between vehicle systems that share at least one common characteristic in an ordered sequence of streaming data. In one embodiment, data elements or vehicle system data that are similar receive a low score, or a determination is made that the vehicle system is not a candidate vehicle system for repair or maintenance. On the other hand, if a vehicle system with a common characteristic also has different vehicle system data, a high score may be provided due to data inconsistencies. This score can be used to identify candidate vehicle systems (for repair or maintenance). In this way, the control system uses the comparison method to find differences between portions of the data streams and does not require prior determination or knowledge (i.e., artificial intelligence) of the nature of anomalies that may exist in the vehicle system data. Furthermore, the comparison method avoids the use of processing dependencies between data elements, allowing for straightforward parallel implementation of each data element. Instead, the control system searches for anomalous patterns in data streams (e.g., vehicle system data), which may include audio signals, health screening, geographic data, etc.

[0051] In particular, identifying or determining whether a vehicle system is healthy or unhealthy can be based on relativity under similar conditions. In cases where a huge amount of sensor data is provided across various fleets, vehicle systems, etc., comparing vehicle system data from similarly operating systems can identify candidate vehicle systems for repair or maintenance. Typically, sensor information is raw data, which may not generally be useful for determining anomalies because the data may be meaningless without context. For example, if the engine temperature of a first vehicle system is 5°C higher than the engine temperature of a second vehicle system, 5°C may or may not be significant. While such a difference may be significant if the vehicle systems are in the same environment, a vehicle system with a 5°C higher engine temperature may be insignificant because it is in a 20°C higher environment. As a result, using the acquired huge data sets can make it difficult to develop robust machine learning-based models due to unit-to-unit variations (e.g., mechanical, design, environmental, etc.). However, a control system and method for finding vehicle system anomalies built on comparing various parameters of vehicle systems sharing common characteristics is provided. For example, four vehicle systems may share a common characteristic of being in the same environment (e.g., the same 25-mile radius, 50-mile radius, 100-mile radius, etc.) and thus traveling in the same geographic location. If one of the vehicle systems' operational systems behaves differently compared to other vehicle systems in the same environment, the vehicle system with the differently behaving operational system may be identified as a candidate vehicle system for repair or maintenance. Communications may then be provided to initiate maintenance and repair of the candidate vehicle system to address the anomaly as quickly as possible and prevent damage as a result of the malfunctioning operational system.

[0052] In some exemplary embodiments, a system is provided that includes a controller having one or more processors. The one or more processors may be configured to: acquire first vehicle system data from a first vehicle system of the plurality of vehicle systems based on a common characteristic shared by the plurality of vehicle systems; and acquire second vehicle system data from a second vehicle system of the plurality of vehicle systems, the second vehicle system data being based on the common characteristic shared by the two or more vehicle systems. The one or more processors may also be configured to compare the first vehicle system data with the second vehicle system data and identify one of the first vehicle system or the second vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the second vehicle system data.

[0053] Optionally, the common characteristic may be based on distance from the geographic location. In one aspect, the one or more processors may also be configured to compare the first vehicle system data with the second vehicle system data by comparing the first vehicle system data and the second vehicle system data with additional vehicle system data of one or more additional vehicle systems of the plurality of vehicle systems. The additional vehicle system data may be based on the common characteristic. In another aspect, the first vehicle system data may be associated with an operation system of the first vehicle system, and the second vehicle system data may be associated with an operation system of the second vehicle system. Additionally, the operation system of the first vehicle system may be associated with an operation system of the second vehicle system. In one example, the one or more processors may be further configured to communicate a message associated with the candidate vehicle systems to a remote controller. Optionally, the remote controller may be a maintenance controller configured to schedule maintenance of the first vehicle system or a dispatch controller configured to schedule maintenance of the first vehicle system. In another example, the common characteristic may be at least one of an engine type, an engine manufacturer, an age of the vehicle system, a mileage of the vehicle system, or a route of the vehicle system. In one embodiment, the one or more processors may be further configured to search for and identify one or more additional vehicle systems of the plurality of vehicle systems based on the common characteristic before acquiring the first vehicle system data and the second vehicle system data. Optionally, the one or more processors may be further configured to determine whether a threshold number of the one or more additional vehicle systems have been identified in response to searching for the additional vehicle systems, vary the common characteristic in response to the threshold number of vehicle systems not being identified, and perform an additional search of the one or more additional vehicle systems after varying the common characteristic.

[0054] In another exemplary embodiment, a system may include a controller having one or more processors. The one or more processors may be configured to acquire first vehicle system data from a first vehicle system in a determined area and acquire additional vehicle system data from a plurality of additional vehicle systems in the determined area. The one or more processors may also be configured to compare the first vehicle system data with the additional vehicle system data and identify the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the additional vehicle system data.

[0055] Optionally, the determined region may be a determined radius from the determined location. In one aspect, the plurality of additional vehicle systems may include at least two vehicle systems. In another aspect, the first vehicle system data may be associated with an operation system of the first vehicle system. In one example, the system may also include a sensor coupled to the operation system. In particular, the first vehicle system data may be obtained from the sensor. In another example, the one or more processors may be further configured to communicate the first vehicle system data to a remote controller in response to identifying the first vehicle system as a candidate vehicle system. In another example, the first vehicle system may be one of an automobile, a rail vehicle, a water vehicle, or an air vehicle.

[0056] In one or more additional embodiments, a method may be provided that includes searching for and identifying vehicle systems based on a common characteristic and determining whether a threshold number of vehicle systems have been identified during the search. The method may also include varying the common characteristic in response to the threshold number of vehicle systems not being identified and performing an additional search after varying the common characteristic. The method may also include acquiring first vehicle system data associated with a first operating system from a first vehicle system identified in the additional search, acquiring additional vehicle system data associated with additional operating systems of the plurality of additional vehicle systems identified in the additional search, where the first operating system is associated with the additional operating system, and identifying the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the additional vehicle system data.

[0057] Optionally, the common characteristic may be a defined region. In one aspect, varying the common characteristic in response to a threshold number of the plurality of additional vehicle systems not being identified may include increasing a size of the defined region. In another aspect, the method may also include communicating the first vehicle system data to a remote controller in response to identifying the first vehicle system as a candidate vehicle system.

[0058] In one or more additional embodiments, a system may include a controller having one or more processors. The one or more processors may acquire a plurality of first corresponding data sets from the plurality of vehicle systems based on a plurality of first common characteristics shared by the plurality of vehicle systems, and may acquire a plurality of second corresponding data sets from the plurality of vehicle systems based on the plurality of first common characteristics and / or a plurality of second common characteristics shared by the plurality of vehicle systems. The one or more processors may also repeatedly compare individual data sets of the plurality of first corresponding data sets for each of the plurality of vehicle systems to determine whether each individual data set of the plurality of first corresponding data sets is outside a first specified deviation threshold with respect to other data sets of the plurality of first corresponding data sets. The one or more processors may also repeatedly compare individual data sets of the plurality of second corresponding data sets for each of the plurality of vehicle systems to determine whether each individual data set of the plurality of second corresponding data sets is outside a second specified deviation threshold with respect to other data sets of the plurality of second corresponding data sets. The one or more processors may also identify a first vehicle system of the plurality of vehicle systems as a candidate for a maintenance or repair action in response to determining that the individual data sets of the first vehicle system are outside the first and second specified deviation thresholds, respectively. The one or more processors may also control at least one of the first vehicle system or the electronic device in response to identifying the first vehicle system as a candidate.

[0059] In some exemplary embodiments, the device performs one or more processes described herein. In some exemplary embodiments, the device performs these processes based on a processor executing software instructions stored by a computer-readable medium, such as a memory and / or storage component. A computer-readable medium (e.g., a non-transitory computer-readable medium) is defined herein as a non-transitory memory device. A memory device includes a memory space located within a single physical storage device or a memory space spread across multiple physical storage devices.

[0060] Software instructions may be loaded into the memory and / or storage component from another computer-readable medium or from another device via a communications interface. When executed, the software instructions stored in the memory and / or storage component cause the processor to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, the embodiments described herein are not limited to any specific combination of hardware circuitry and software.

[0061] As used herein, the terms “processor” and “computer,” as well as related terms such as “processing device,” “computing device,” and “controller,” may refer to, but are not limited to, integrated circuits referred to in the art as computers, including microcontrollers, microcomputers, programmable logic controllers (PLCs), field programmable gate arrays, and application-specific integrated circuits, as well as other programmable circuits. Suitable memory may include, for example, computer-readable media. The computer-readable media may be, for example, computer-readable non-volatile media such as random access memory (RAM), flash memory, etc. The term “non-transitory computer-readable media” refers to tangible, computer-based devices implemented for short-term and long-term storage of information such as computer-readable instructions, data structures, program modules and sub-modules, or other data within any device. Accordingly, the methods described herein may be encoded as executable instructions embodied in tangible, non-transitory computer-readable media, including, but not limited to, storage and / or memory devices. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein. Thus, the term includes tangible computer-readable media, including but not limited to non-transitory computer storage devices, including but not limited to volatile and non-volatile media, as well as removable and non-removable media such as firmware, physical and virtual memory, CD-ROMs, DVDs, and other digital sources such as a network or the Internet.

[0062] The singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. "Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and that the description may include cases where the event occurs and cases where it does not occur. As used throughout this specification and claims, approximation language may be applied to modify any quantitative expression that may permissibly vary without resulting in a change in the basic function to which it may relate. Thus, values ​​modified by terms such as "about," "substantially," and "approximately" or terms may not be limited to the exact value specified. In at least some cases, approximation language may correspond to the precision of an instrument for measuring the value. Throughout this specification and claims, unless the context or language dictates otherwise, range limitations may be combined and / or interchanged, and such ranges may be specified and include all subranges contained therein.

[0063] This written description uses examples to disclose embodiments, including the best mode, and also enables any person skilled in the art to practice the embodiments, including making and using any device or system and performing any incorporated methods. The claims define the patentable scope of the disclosure, and include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that differ from the literal words of the claims, or if they include equivalent structural elements that differ substantially from the literal words of the claims.

Claims

1. 1. A system comprising: a controller having one or more processors, the one or more processors acquiring first vehicle system data from a first vehicle system of the plurality of vehicle systems based on a common characteristic shared by the plurality of vehicle systems; acquiring second vehicle system data from a second vehicle system of the plurality of vehicle systems, the second vehicle system data being based on the common characteristic shared by two or more vehicle systems; comparing the first vehicle system data with the second vehicle system data; and identifying one of the first vehicle system or the second vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the second vehicle system data.

2. The system of claim 1 , wherein the common characteristic is based on distance from a geographic location.

3. 2. The system of claim 1, wherein the one or more processors are configured to compare the first vehicle system data with the second vehicle system data by comparing the first vehicle system data and the second vehicle system data with additional vehicle system data for one or more additional vehicle systems of the plurality of vehicle systems, the additional vehicle system data being based on the common characteristic.

4. 2. The system of claim 1, wherein the first vehicle system data is associated with an operating system of the first vehicle system, the second vehicle system data is associated with an operating system of the second vehicle system, and the operating system of the first vehicle system is associated with the operating system of the second vehicle system.

5. the one or more processors: The system of claim 1 , further configured to communicate a message to a remote controller associated with the candidate vehicle system.

6. The system of claim 5 , wherein the remote controller is a maintenance controller configured to schedule maintenance of the first vehicle system or a dispatch controller configured to schedule maintenance of the first vehicle system.

7. The system of claim 1 , wherein the common characteristic is at least one of an engine type, an engine manufacturer, an age of the vehicle system, a mileage of the vehicle system, or a route of the vehicle system.

8. the one or more processors:

2. The system of claim 1, further configured to search for and identify one or more additional vehicle systems of the plurality of vehicle systems based on the common characteristic before acquiring the first vehicle system data and the second vehicle system data.

9. the one or more processors: determining whether a threshold number of the one or more additional vehicle systems have been identified in response to searching for the additional vehicle systems; varying the common characteristic in response to the threshold number of vehicle systems not being identified; The system of claim 8 , further configured to: after varying the common characteristic, perform an additional search on the one or more additional vehicle systems.

10. 1. A system comprising: a controller having one or more processors, the one or more processors acquiring first vehicle system data from a first vehicle system in the determined region; acquiring additional vehicle system data from a plurality of additional vehicle systems in the determined area; comparing the first vehicle system data with the additional vehicle system data; and identifying the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data with the additional vehicle system data.

11. The system of claim 10 , wherein the determined area is a determined radius from a determined location.

12. The system of claim 10 , wherein the plurality of additional vehicle systems includes at least two vehicle systems.

13. The system of claim 10 , wherein the first vehicle system data relates to an operating system of the first vehicle system.

14. The system of claim 13 , further comprising a sensor coupled to the operating system, wherein the first vehicle system data is obtained from the sensor.

15. 11. The system of claim 10, wherein the one or more processors are further configured to communicate the first vehicle system data to a remote controller in response to identifying the first vehicle system as the candidate vehicle system.

16. the one or more processors: acquiring the additional vehicle system data from the plurality of additional vehicle systems based on a determination that the plurality of additional vehicle systems and the first vehicle system share a plurality of common characteristics; comparing the first vehicle system data with the additional vehicle system data to determine whether the first vehicle system data is outside a specified deviation threshold of the additional vehicle system data; identifying the first vehicle system as the candidate vehicle system for maintenance in response to determining that the first vehicle system data is outside the specified deviation threshold; 11. The system of claim 10, further configured to: control at least one of the first vehicle system or an electronic device in response to identifying the first vehicle system as the candidate vehicle system.

17. 1. A method comprising: performing a search to identify vehicle systems based on common characteristics; determining whether a threshold number of vehicle systems have been identified during said search; varying the common characteristic in response to the threshold number of vehicle systems not being identified; performing an additional search after varying the common characteristic; obtaining first vehicle system data associated with a first operating system from a first vehicle system identified in the additional search; obtaining additional vehicle system data associated with additional operating systems of the plurality of additional vehicle systems identified in the additional search, the first operating system associated with the additional operating systems; and identifying the first vehicle system as a candidate vehicle system for maintenance based on comparing the first vehicle system data to the additional vehicle system data.

18. The method of claim 17 , wherein the common characteristic is a defined region.

19. 20. The method of claim 18, wherein, in response to the threshold number of multiple additional vehicle systems not being identified, varying the common characteristic comprises increasing a size of the defined region.

20. The method of claim 17 , further comprising, in response to identifying the first vehicle system as the candidate vehicle system, communicating the first vehicle system data to a remote controller.

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