System and method for evaluating repair of assets

Abstract

To provide a system and a method for evaluating maintenance or repair needed for a fleet of remotely operated assets such as a fleet of vehicle systems.SOLUTION: The system includes a processor to receive vehicle data from a vehicle system at a first location and communicate the data to a second location. The processor integrates the data into a database of diagnostic data at the second location and identifies a diagnostic code that indicates an expected operation of the vehicle system or an unexpected operation. The processor determines a maintenance operation based on the diagnostic code. The method includes receiving vehicle data from a vehicle system at a first location and communicating the vehicle data to the second location. The method includes integrating the vehicle data into a database of first diagnostic data and identifying a diagnostic code that indicates whether the vehicle data represents an expected operation of the vehicle system or an unexpected operation of the vehicle system. The method includes determining a maintenance operation based on the code.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The disclosed subject matter relates to systems and methods for evaluating the repair of a fleet of assets.

Background Art

[0002] To operate a fleet of assets that work remotely, such as a fleet of vehicle systems, the assets need to be maintained or repaired at a service center. Vehicle systems can enter a service center for scheduled or unscheduled maintenance or repair. Technicians at the service center can perform unscheduled maintenance according to instructions sent from a remote diagnostic center. When the maintenance work is completed, the technician can test the vehicle system using software provided on the vehicle system. If the software of the vehicle system indicates that the vehicle system has been adequately maintained or repaired, the vehicle system may be approved to return to operation. However, the software on the vehicle system may have limited capabilities and may not be updated frequently enough to reflect new diagnostic information or techniques. A vehicle system undergoing unscheduled maintenance may be determined by the vehicle system software to have been adequately maintained or repaired, but due to the limited capabilities of the vehicle system software, there is a possibility that the vehicle system may not be fully maintained or repaired when it returns to operation.

Summary of the Invention

Problems to be Solved by the Invention

[0003] There may be a desire to have systems and methods different from currently available systems and methods.

Means for Solving the Problems

[0004] In one example or embodiment, a system of one or more processors can receive vehicle data from a vehicle system at a first location and transmit the vehicle data from the first location to a second location. The processor can integrate the vehicle data at the second location into a database of first diagnostic data and identify one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work of the vehicle system. Based on one or more first diagnostic codes, the processor can determine one or more maintenance tasks to be performed on the vehicle system.

[0005] In one example or embodiment, the method may include receiving vehicle data from a vehicle system at a first location and transmitting the vehicle data from the first location to a second location far from the first location. The method may include integrating the vehicle data at the second location into a database of first diagnostic data and identifying one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work of the vehicle system. The method may include determining one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes.

[0006] In one example or embodiment, the system may include one or more first processors located at a first location and one or more second processors located at a second location far from the first location. One or more first processors may collect vehicle data from a vehicle system at the first location and transmit the vehicle data to one or more second processors. One or more second processors may integrate the vehicle data into a database of first diagnostic data at the second location and identify one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work of the vehicle system. One or more second processors may determine one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes. [Brief explanation of the drawing]

[0007] The subject matter can be understood by referring to the attached drawings and reading the following description of non-limiting embodiments.

[0008] [Figure 1] This is a schematic diagram illustrating a system according to one embodiment. [Figure 2] This is a schematic diagram illustrating a system according to one embodiment. [Figure 3] This figure schematically illustrates a method according to one embodiment. [Figure 4] This figure schematically illustrates a method according to one embodiment. [Modes for carrying out the invention]

[0009] Embodiments of the subject matter described herein relate to systems and methods for evaluating the maintenance or repair required for a fleet of remotely operated assets, such as a fleet of vehicle systems. The systems and methods also provide an evaluation of the effectiveness of maintenance or repair performed before a vehicle system is returned to operation. The systems and methods provide communication between remote diagnostic personnel who scrutinize historical diagnostic data of a fleet of vehicle systems and service center technicians who perform initial diagnostics of the vehicle systems based on sensor data from the vehicle systems acquired while in operation or at a service center. From the sensor data, the service center technicians can identify faults of components, systems, and / or components or systems of the vehicle systems that indicate the vehicle system is working unexpectedly. The service center technicians can identify one or more causes of the unexpected work.

[0010] Remote diagnostic center personnel can receive vehicle system sensor data and one or more causes (labeled as sub-identification codes) from the service center. The remote diagnostic center can access historical vehicle system diagnostic data from the vehicle system and other vehicle systems in the fleet. The remote service center includes the vehicle system sensor data and sub-identification codes in a database of historical vehicle system diagnostic data and identifies one or more first-level diagnostic codes from the database. The first-level diagnostic codes indicate the components of the vehicle system and whether the system is working in an expected, possibly unexpected, or unexpected way. The remote diagnostic center can create a review of the vehicle system and initiate communication with the service center to consider possible servicing or repair. The communication may include a discussion of the initial diagnosis performed by the service center, possible servicing and / or repair, and solutions, if any, that may involve servicing and repair work before releasing the vehicle system back into operation. The remote diagnostic center can provide a score for the process based on the process from when the vehicle system arrives at the service center until it is released from the service center for reporting and / or analysis.

[0011] One or more embodiments are described in relation to railway vehicle systems, but not all embodiments are limited to railway vehicle systems. Unless expressly denied or otherwise specified, the subject matter described herein extends to other types of vehicle systems, such as automobiles, trucks (with or without trailers), buses, ships, aircraft, mining vehicles, agricultural vehicles, or other off-highway vehicles. Vehicle systems described herein (railway vehicle systems or other vehicle systems that do not run on rails or tracks) may consist of a single vehicle or multiple vehicles. With respect to multiple vehicle systems, the vehicles may be mechanically coupled to one another (e.g., by couplers), or logically coupled, but not mechanically coupled. For example, vehicles may be logically coupled but not mechanically coupled when separate vehicles communicate with each other to coordinate their movements so that the vehicles run together (e.g., as a convoy).

[0012] Referring to Figure 1, a system 10 is provided for evaluating the repair of a fleet of remote assets. The fleet of remote assets may include a fleet of vehicle systems such as railcars 12 and / or trucks 26. The system enables a wide variety of users to obtain information about each of the mobile assets. According to one embodiment, user 14 may include a transport company that owns and / or operates the remote assets. According to one embodiment, user 24 may include a customer of the transport company. According to one embodiment, the user may include personnel in an asset service center 22 (e.g., a service workshop) and / or personnel in a remote diagnostic center 18. According to one embodiment, the user may include operators (e.g., train engineers or truck drivers) who operate each individual asset.

[0013] The remote diagnostic center and the service center can both be linked to the network 15 by a known type of data connection. According to one embodiment, the network is a global network such as the Internet, and the remote diagnostic center and the service center can each be linked to the network by a computer interface through an Internet service provider. The network provides a means for communication between the remote diagnostic center and the service center. The remote diagnostic center and the service center can also communicate with users such as shipping companies through the network. Other users can communicate with the remote diagnostic center and / or the service center through a link to the network.

[0014] Each mobile asset may be equipped with a location determination system 16. In one embodiment, the location determination system may be a Global Navigation Satellite System (GNSS) receiver, such as a Global Positioning System (GPS) receiver, or other satellite-based or local navigation equipment for determining the geographical location of the mobile asset. Data regarding the location of the mobile asset and the mobile asset's operating parameters may be transmitted periodically or simultaneously from the remote asset to a telediagnostic center by a communication system 25 via a data link 20, such as a satellite system, cellular system, optical or infrared system, or hardwired telephone line. The asset's communication system may include transceivers for transmitting information, including location information and operating parameters, and for receiving information from other devices and users within the system.

[0015] A service center may include one or more computers 21 and / or one or more mobile devices 23. One or more mobile devices may be smartphones, tablets, or personal digital assistants. The computers and one or more mobile devices of one or more service centers may be connected to a network, for example, through an internet service provider or a cellular service provider. One or more computers and / or one or more mobile devices may communicate with each asset, other devices or users of the system, and / or a remote diagnostic center via data links.

[0016] A service center may perform scheduled maintenance on a vehicle system and / or perform unscheduled maintenance on a vehicle system that has arrived at the service center. A vehicle system may arrive at the service center on a scheduled basis or on an unscheduled basis. A vehicle system may arrive on an unscheduled basis so that the operator of the vehicle system can determine that the vehicle system is operating in an unexpected manner. For example, a sensor may notify the operator that the operating parameters of the vehicle system indicate that the vehicle system is not operating in an expected manner. Maintenance work performed may include the replacement of parts and / or systems of the vehicle system that are scheduled to be replaced due to age and / or use of the parts and / or systems. Maintenance work performed may include repair work to replace damaged and / or malfunctioning parts and / or systems. Repair work may include the repair or replacement of parts and / or systems.

[0017] Referring to Figure 2, each vehicle system may be equipped with a sensor system 32 that includes multiple sensors for monitoring multiple working parameters representing the state and operational efficiency of the vehicle system. Sensors may include temperature sensors that detect the temperature of parts, components, and / or the system of the vehicle system. Temperature sensors may detect the temperature of fluids in the vehicle system, such as lubricating oil. Sensors may include pressure sensors that detect pressure. For example, a pressure sensor may detect the pressure of brake fluid in a brake system. Sensors may include voltage sensors and / or current sensors that detect the voltage and / or current of the vehicle system. For example, one or more sensors may determine the voltage and / or current supplied by the vehicle system's battery or battery bank. As used herein, the term “sensor” may include any sensor that detects or detects any characteristic or working parameter of a vehicle system, and the term “sensor system” may include any sensor system or one or more sensor systems that detect or detect characteristics or working parameters of a vehicle system.

[0018] The vehicle system's sensor system can detect the characteristics and working parameters of the vehicle system when the vehicle system is working outside of a service center. The vehicle system may include a memory to store sensor readings when the vehicle system is working, for example, within a traffic network. The vehicle system may include a control system or controller 28 that controls the work of the vehicle system. The controller can execute one or more feedback control loops to cause the vehicle system to work within one or more working parameters. The controller can generate diagnostic data indicating that one or more working parameters exceed one or more thresholds. The diagnostic data of the vehicle system may be stored in the vehicle system's memory. According to one embodiment, the controller executes one or more feedback control loops for one or more throttle settings of the vehicle system and generates and stores diagnostic data for one or more throttle settings.

[0019] The service center may include a sensor system 34 that can be provided to the vehicle system when the vehicle system arrives at the service center. The service center's sensor system may be provided to a vehicle system that is located at the service center and does not include sensors for detecting some characteristics or working parameters of the vehicle system. For example, the service center's sensor system may include multiple sensors, which are connected to each other, for example by a wire harness, and are placed on the vehicle system to detect or sense characteristics or working parameters of the vehicle system in locations not detected or perceived by the vehicle system's sensor system, or for components or systems. The service center's sensor system may acquire sensor data from the vehicle system while the vehicle system is idling at the service center. The service center's sensor system may acquire sensor data from the vehicle system at other working levels of the vehicle system while the vehicle system is at the service center.

[0020] The service center may include one or more processors 36. One or more processors may be located within the service center's computer and / or mobile device. The service center's computer and / or mobile device may include a display 38 and inputs 40 that can be used by service center personnel to cause one or more processors to execute instructions stored in memory 42.

[0021] When a vehicle system arrives at a service center, the vehicle system's sensor systems and / or sensor data from the vehicle system's sensor systems may be transmitted to or transmitted to the service center's computer and / or mobile device. Sensor data may be communicated or transmitted wirelessly, for example, via a network link or data link. Sensor data may also be transmitted to a computer and / or handheld device via a wired connection. The computer and / or handheld device may store the sensor data in the computer and / or handheld device's memory. One or more processors in the computer and / or handheld device may run or launch a software program that examines the sensor data and determines whether any of the sensor data indicates the presence of a fault. For example, sensor data may indicate that one or more components or systems of the vehicle system are malfunctioning or not working with expected parameters. One or more processors may determine one or more sub-identifications of a fault from the sensor data. One or more sub-identifications may identify one or more causes of the fault. Fault data, including sensor data and any sub-identifications, may form vehicle diagnostic data that can be used to determine whether the vehicle system requires any maintenance or repair.

[0022] The computer and / or handheld device of the service center can transmit or transfer vehicle diagnostic data to the remote diagnostic center. The remote diagnostic center can include a memory 46 and one or more processors 44. The memory can include instructions executable by one or more processors to implement the methods or portions of the methods disclosed herein. The memory can store the vehicle diagnostic data of the vehicle system transmitted or transferred from the service center.

[0023] The remote service center can include a database 52 of historical diagnostic data. The historical diagnostic data can include sensor data and fault data from previous service operations on the vehicle system and other vehicle systems from the service center and / or other service centers. The historical diagnostic data can include data regarding maintenance and / or repairs previously performed on the vehicle system by the service center and / or other service centers and / or performed on other vehicles. One or more processors of the remote diagnostic center can integrate the vehicle diagnostic data stored in the memory into the historical diagnostic database.

[0024] One or more processors can insert one or more diagnostic codes indicating that the vehicle system is operating in an expected manner, a possibly expected manner, or an unexpected manner into the vehicle diagnostic data. One or more processors can, for example, determine that the vehicle system is operating in an expected manner although a component or system of the vehicle system may be operating in an unexpected manner. As another example, one or more processors of the remote diagnostic center can determine that one or more components or systems of the vehicle system are operating in a possibly unexpected and / or unexpected manner and that the vehicle system is operating in a possibly unexpected or unexpected manner.

[0025] One or more processors of the remote diagnosis center can determine that the maintenance of the vehicle system requires review by the service center and the remote diagnosis center based on one or more diagnostic codes from the vehicle diagnosis data and the historical diagnosis data. Personnel at the remote diagnosis center can review the sensor data from the vehicle system and the diagnostic review of the vehicle sensor data performed at the service center during the audit. One or more processors of the remote diagnosis center can initiate communication with the service center to provide a discussion between the personnel at the remote diagnosis center and the service center. The communication can be, for example, a chat function between a computer and / or a handheld device at the remote diagnosis center and a computer and / or a handheld device at the service center that provides written communication between the remote diagnosis center and the service center. The communication can be, for example, a video conference between the remote diagnosis center and the service center.

[0026] Referring to FIG. 3, a method 300 according to one embodiment can include a step 310 of uploading vehicle data from a vehicle system to a computing device such as a computer handheld device of a service center. The vehicle data can include sensor data obtained during operation of the vehicle system before arriving at the service center or from operation of the vehicle system at the service center. The sensor data can be obtained from sensors provided on the vehicle system during operation before arriving at the service center or from sensors provided on the vehicle system after arriving at the service center. The method can include a step 320 of determining from the vehicle data one or more malfunctions in the operation of one or more components or systems of the vehicle system and one or more sub-identifications of one or more possible causes of the one or more malfunctions.

[0027] The method may include step 330, which integrates vehicle data and sub-identifications into a diagnostic data database at a remote diagnostic center located far from the service center. The diagnostic data database may include vehicle data from vehicle systems that were previously at the service center, as well as vehicle systems that are currently at the service center. The method may include step 340, which identifies diagnostic codes from the vehicle data and sub-identifications and inserts the diagnostic codes into the database. Diagnostic codes indicate that the vehicle system is operating in an expected, possibly unexpected, or otherwise unpredictable manner.

[0028] The method may include stop 350, which initiates a case for review with a technician at a service center at a remote diagnostic center. The method may include step 360, which reviews vehicle data uploaded at the service center and sub-identifiers that can determine the cause of one or more failures in one or more components or in the operation of the vehicle system. The method may include step 370, which initiates communication between the remote diagnostic center and the service center. The communication may include a discussion of the vehicle data and the determination of the failures and their sub-identifiers determined at the service center. The communication may include a discussion of the maintenance and repair work to be performed on the vehicle system.

[0029] The method may include a step 380 for determining the release of a vehicle system from a service center. The release decision may include documentation of communications between the service center and a remote diagnostic center. The decision may include a decision on any maintenance or repair work to be performed on the vehicle system and the effectiveness of the maintenance or repair work. The method may include a step 390 for scoring the process in order to document the decision to release the vehicle system from the service center. The score may be reported to the owner or user of the vehicle system to report the release and to enable an analysis of the process from when the vehicle system arrived at the service center until it was released from the service center.

[0030] Referring to Figure 4, a method 400 according to one embodiment may include the steps of: collecting vehicle data from a vehicle system at a first location; and transmitting the vehicle data from the first location to a second location far away from the first location. The method may also include the steps of: integrating the vehicle data at the second location into a database of first diagnostic data at the second location; and identifying one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work on the vehicle system. The method may also include the step of determining one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes.

[0031] According to one embodiment, the method may include performing either or both repair work on a vehicle system based on one or more sub-identification pieces of information identified from vehicle system data collected during operation of the vehicle system and / or during operation within a service center. Repair and / or replacement work may be based on one or more diagnostic codes from a database of diagnostic data. Repair and / or replacement work may be based on a score for the release of the vehicle system from the service center. For example, according to one embodiment, components or systems such as pumps, sensors, valves, circuits, or parts of a brake system or throttle system can be repaired. According to one embodiment, components or systems can be replaced.

[0032] Integrating vehicle data and one or more fault sub-identifications into a database improves the system's ability to determine one or more diagnostic codes that correctly identify the required servicing and / or repair. The database can include data from similar vehicle systems with similar fault sub-identifications that provide more accurate decisions regarding the servicing, repair, or replacement required for vehicle systems at the service center. Using artificial intelligence (AI) and / or machine learning (ML) techniques, processors may be able to identify the required servicing, repair, or replacement more quickly than currently available methods and systems. Scrutinizing the upload of vehicle system data from the service center and the determination of one or more fault sub-identifications by one or more processors at the remote diagnostic center can improve the identification and insertion of one or more diagnostic codes, enabling scrutiny of parametric data of vehicle system data at the remote diagnostic center. Determining a score for the release of vehicle systems from the service center can provide improved diagnostics, resulting in fewer recurring failures of vehicle systems.

[0033] The system may include a system of one or more processors for receiving vehicle data from a vehicle system at a first location and transmitting the vehicle data from the first location to a second location. One or more processors may integrate the vehicle data at the second location into a database of first diagnostic data and identify one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work of the vehicle system. One or more processors may determine one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes.

[0034] Vehicle data may include sensor data collected from sensors while the vehicle system is in operation.

[0035] Sensor data can be collected while the vehicle system is idling.

[0036] Sensor data can be collected at a specified throttle setting in the vehicle system.

[0037] Vehicle data can be a secondary source of diagnostic data from the vehicle's systems.

[0038] The second set of diagnostic data can be obtained from the feedback loop of the vehicle system's control system.

[0039] The second set of diagnostic data can indicate whether one or more operational parameters of the vehicle system exceed a threshold.

[0040] One or more processors may include algorithms configured to identify one or more first diagnostic codes.

[0041] The algorithm may be configured to determine one or more maintenance tasks.

[0042] One or more processors can initiate communication between the first location and the second location.

[0043] One or more processors may receive from the second location a score based on one or more of the following: second diagnostic data determined at the first location, communication between the first and second locations, determination of one or more maintenance tasks, or completion of one or more maintenance tasks.

[0044] The method may include receiving vehicle data from a vehicle system at a first location and transmitting the vehicle data from the first location to a second location far away from the first location. The method may also include integrating the vehicle data at the second location into a database of first diagnostic data and identifying one or more first diagnostic codes from the database that indicate whether the vehicle data represents expected work or unexpected work of the vehicle system. The method may also include determining one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes.

[0045] Vehicle data may include sensor data collected from sensors while the vehicle system is in operation.

[0046] Sensor data can be collected while the vehicle system is idling.

[0047] Sensor data can be collected at a specified throttle setting in the vehicle system.

[0048] Vehicle data can be a secondary source of diagnostic data from the vehicle's systems.

[0049] The second set of diagnostic data can be obtained from the feedback loop of the vehicle system's control system.

[0050] The second set of diagnostic data can indicate whether one or more operational parameters of the vehicle system exceed a threshold.

[0051] This method may include executing an algorithm configured to identify one or more first diagnostic codes.

[0052] The algorithm can determine one or more maintenance tasks.

[0053] This method may include the first location initiating communication with the vehicle system or one or both of the second locations.

[0054] This method may include receiving from the second location a score based on one or more of the following: second diagnostic data determined at the first location, communication between the first and second locations, determination of one or more maintenance tasks, or completion of one or more maintenance tasks.

[0055] The system may include one or more first processors at a first location and one or more second processors at a second location. The second location may be far from the first location. One or more first processors may receive vehicle data from a vehicle system at the first location and transmit the vehicle data to one or more second processors. One or more second processors may integrate the vehicle data into a database of first diagnostic data at the second location and identify one or more first diagnostic codes from the database indicating whether the vehicle data represents expected work or unexpected work of the vehicle system. One or more second processors may determine one or more maintenance tasks to be performed on the vehicle system based on one or more first diagnostic codes.

[0056] Vehicle data may include sensor data collected from sensors while the vehicle system is in operation.

[0057] One or more first processors can determine second diagnostic data from the vehicle system.

[0058] The second set of diagnostic data can be obtained from the feedback loop of the vehicle system's control system.

[0059] The second set of diagnostic data can indicate whether one or more operational parameters of the vehicle system exceed a threshold.

[0060] One or more second processors may include an algorithm for identifying one or more first diagnostic codes.

[0061] The algorithm can determine one or more maintenance tasks.

[0062] One or more second processors are configured to initiate communication with one or more first processors.

[0063] One or more second processors may receive from a second location a score based on one or more of the following: second diagnostic data determined by one or more first processors, communication between one or more first processors and one or more second processors, determination of one or more maintenance tasks, or completion of one or more maintenance tasks.

[0064] In one embodiment, the controller or system described herein may have a deployed local data collection system and may use machine learning to enable derivation-based learning results. The controller may learn from and determine a dataset (including data provided by various sensors) by performing data-driven predictions and fitting them according to the dataset. In various embodiments, machine learning may include performing multiple machine learning tasks by a machine learning system such as supervised learning, unsupervised learning, and reinforcement learning. Supervised learning may include presenting a set of input examples and a desired output to the machine learning system. Unsupervised learning may include a learning algorithm that structures its input by methods such as pattern detection and / or feature learning. Reinforcement learning may include the machine learning system running in a dynamic environment and then providing feedback on correct and incorrect decisions. In various examples, machine learning may include multiple other tasks based on the output of the machine learning system. In various examples, the tasks may be machine learning problems such as classification, regression, clustering, density estimation, dimensionality reduction, and anomaly detection. In various examples, machine learning may include multiple mathematical and statistical techniques. In various examples, many types of machine learning algorithms can include decision tree-based learning, correlation rule learning, deep learning, artificial neural networks, genetic learning algorithms, guided logic programming, support vector machines (SVMs), Bayesian networks, reinforcement learning, representation learning, rule-based machine learning, sparse dictionary learning, similarity and metric learning, learning classifier systems (LCS), logistic regression, random forests, K-means, gradient boosting, K-nearest neighbors (KNNs), and a priori algorithms. In various embodiments, a particular machine learning algorithm may be used (for example, to solve both constrained and unconstrained optimization problems that can be based on natural selection). In one example, an algorithm may be used to address a mixed-integer programming problem where some components are restricted to integer values.Algorithms, machine learning techniques, and machine learning systems can be used in computational intelligence systems, computer vision, natural language processing (NLP), recommendation systems, reinforcement learning, graphical model building, and more. For example, machine learning can be used to perform decisions, calculations, comparisons, and behavioral analysis.

[0065] In one embodiment, the controller may include a policy engine that can apply one or more policies. These policies may be based at least in part on the characteristics of a given item of equipment or environment. With respect to control policies, the neural network may receive inputs of several environmental and task-related parameters. These parameters may include, for example, operational inputs related to work equipment, data from various sensors, location and / or positional data. The neural network can be trained to generate outputs based on these inputs, the outputs representing the actions or sets of actions that the equipment or system should take to achieve the work objective. During operation in one embodiment, decisions can be made by processing the inputs through the parameters of the neural network to generate values ​​at the output node that designate the action as the desired action. This action can be converted into a signal that causes the vehicle to work. This can be achieved by backpropagation, a feedforward process, closed-loop feedback, or open-loop feedback. Alternatively, the controller's machine learning system may use evolutionary strategy techniques to tune various parameters of the artificial neural network instead of using backpropagation. The controller can use a neural network architecture with functions that may not always be solvable using backpropagation, such as non-convex functions. In one embodiment, the neural network has a set of parameters representing the weights of its node connections. Several copies of this network are generated, then different tunings are made to the parameters, and simulations are performed. Once outputs are obtained from the various models, these models can be evaluated for their performance using a determined success metric. The best model is selected, and the vehicle controller executes its plan to realize the desired input data and reflect the best-case outcome scenario predicted thereby. Furthermore, the success metric may be a combination of optimized results that can be weighted against each other.

[0066] Where used herein, elements or steps listed in the singular and followed by the word “a” or “an” do not exclude the plural form of such element or step unless such exclusion is expressly stated. Furthermore, references to “one embodiment” of the present invention do not preclude the existence of additional embodiments incorporating the listed features. Furthermore, unless expressly stated to the contrary, embodiments “comprising,” “comprises,” “including,” “includes,” “having,” or “has” one or more elements having a particular characteristic may include additional such elements that do not possess that characteristic. In the appended claims, the terms “including” and “in which” are used as plain English synonyms for the terms “comprising” and “wherein,” respectively. Furthermore, in the following claims, terms such as “first,” “second,” and “third” are used merely as labels and do not impose numerical requirements on their subjects. Furthermore, the following limitation of claims is not intended to be construed under 112(f) of the U.S. Patent Act unless such limitation of claims explicitly uses the phrase “means for” followed by a description of a function lacking further structure.

[0067] The above description is illustrative and not limiting. For example, the embodiments (and / or aspects thereof) described above can be used in combination with one another. Furthermore, many modifications can be made to adapt specific situations or materials to the teachings of the subject without departing from the scope of the subject. The dimensions and types of materials described herein define parameters of the subject, but they are illustrative embodiments. Other embodiments will be apparent to those skilled in the art upon closer examination of the above description. Accordingly, the scope of the subject should be determined by reference to the appendix, along with the entire scope of equivalents to which such claims are granted.

[0068] This specification uses examples to disclose several embodiments of the subject matter, including the best mode, and to enable a person skilled in the art to carry out embodiments of the subject matter, including constructing and using any device or system, and performing any incorporated method. The patentable scope of the subject matter is defined by the claims and may include other examples that a person skilled in the art can conceive. Such other examples are intended to be within the claims if they have structural elements that are not different from the language of the claims, or if they include equivalent structural elements that are not substantially different from the language of the claims.

[0069] References herein to other matters identified in patent documents or prior art should not be construed as an acknowledgment that the documents or other matters were known or that the information contained herein was part of the common general knowledge as of the priority date of any of the claims.

Claims

1. System (10), Vehicle data is received from the vehicle system (12, 26) located at the first location. The vehicle data from the first location is transmitted to the second location. The vehicle data is integrated into the first diagnostic data database (52) at the second location. Identify one or more first diagnostic codes from the database (52) that indicate whether the vehicle data represents expected work or unexpected work of the vehicle system (12, 26), Based on the one or more first diagnostic codes, one or more maintenance tasks to be performed on the vehicle system (12, 26) are determined. One or more processors (36) configured in such a manner, A system (10) comprising the following.

2. The system (10) according to claim 1, wherein the vehicle data includes sensor data received from the sensor (36) during the operation of the vehicle system (12, 26).

3. The system (10) according to claim 2, wherein the sensor data is received from the sensor (36) while the vehicle system (12, 26) is idling.

4. The system (10) according to claim 2, wherein the sensor data is received from the sensor (36) at a specified throttle setting of the vehicle system (12, 26).

5. The system (10) according to claim 1, wherein the vehicle data is second diagnostic data from the vehicle system (12, 26), and the second diagnostic data is received from a feedback loop of the control system (28) of the vehicle system (12, 26).

6. The system (10) according to claim 5, wherein the second diagnostic data indicates whether one or more working parameters of the vehicle system (12, 26) exceed a threshold.

7. The system (10) according to claim 1, wherein the one or more processors (36) include an algorithm configured to identify the one or more first diagnostic codes.

8. The system (10) according to claim 7, wherein the algorithm is configured to determine the one or more maintenance tasks.

9. The system (10) according to claim 1, wherein one or more processors (36) are configured to initiate communication between the first location and the second location.

10. The one or more processors (36) described above, The second diagnostic data determined at the first location, The communication between the first location and the second location, Determination of one or more of the aforementioned maintenance work, Completion of one or more of the maintenance work, A score based on one or more of the above is received from the second location. The system (10) according to claim 9, configured as follows.

11. It is a method, Receiving vehicle data from the vehicle system (12, 26) located at the first location, Transmitting the vehicle data from the first location to a second location located away from the first location, The vehicle data is integrated into the first diagnostic data database (52) at the second location, Identifying one or more first diagnostic codes from the database (52) indicating whether the vehicle data represents expected work or unexpected work of the vehicle system (12, 26), Determining one or more maintenance tasks to be performed on the vehicle system (12, 26) based on the one or more first diagnostic codes, Methods that include...

12. The method according to claim 11, wherein the vehicle data includes sensor data received from a sensor (36) during the operation of the vehicle system (12, 26).

13. The method according to claim 12, wherein the sensor data is received from the sensor (36) while the vehicle system (12, 26) is idling.

14. The method according to claim 12, wherein the sensor data is received from the sensor (36) with a specified throttle setting of the vehicle system (12, 26).

15. The method according to claim 11, wherein the vehicle data is second diagnostic data from the vehicle system (12, 26).

16. The method according to claim 15, wherein the second diagnostic data is obtained from a feedback loop of a control system (28) of the vehicle system (12, 26), and the second diagnostic data indicates whether one or more working parameters of the vehicle system (12, 26) exceed a threshold.

17. System (10), One or more first processors (36) located in the first location, One or more second processors (36) located at a second location away from the first location, It is equipped with, The one or more first processors (36) are configured to receive vehicle data from the vehicle system (12, 26) located at the first location and to transmit the vehicle data to the one or more second processors (36). The one or more second processors (36) described above The vehicle data is integrated into the first diagnostic data database (52) at the second location. Identify one or more first diagnostic codes from the database (52) indicating whether the vehicle data represents expected work or unexpected work of the vehicle system (12, 26), Based on the one or more first diagnostic codes, one or more maintenance tasks to be performed on the vehicle system (12, 26) are determined. A system (10) configured as follows.

18. The system (10) according to claim 17, wherein the vehicle data includes sensor data received from the sensor (36) during the operation of the vehicle system (12, 26).

19. The system (10) according to claim 17, wherein the one or more first processors (36) are further configured to determine second diagnostic data from the vehicle systems (12, 26).

20. The system (10) according to claim 19, wherein the second diagnostic data is received from a feedback loop of the control system (28) of the vehicle system (12, 26) and indicates whether one or more working parameters of the vehicle system (12, 26) exceed a threshold.

Images