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Patent Agency Ranking
公开(公告)号：US11787453B2
公开(公告)日：2023-10-17
申请号：US16561421
申请日：2019-09-05
Applicant: PROGRESS RAIL SERVICES CORPORATION
Inventor： Bradley Howard , John Brand
CPC classification number: B61L27/53 , B61L27/04 , B61L27/40 , B61L27/60 , B61L27/70 , G05B13/0265 , B61L2201/00
Abstract: A machine learning system for maintaining distributed computer control systems for a train may include a data acquisition hub communicatively connected to a plurality of sensors configured to acquire real-time configuration data from one or more of the computer control systems. The machine learning system may also include an analytics server communicatively connected to the data acquisition hub. The analytics server may include a virtual system modeling engine configured to model an actual train control system comprising the distributed computer control systems, a virtual system model database configured to store one or more virtual system models of the distributed computer control systems, wherein each of the one or more virtual system models includes preset configuration settings for the distributed computer control systems, and a machine learning engine configured to monitor the real-time configuration data and the preset configuration settings. The machine learning engine may warn when there is a difference between the real-time configuration data and the preset configuration settings, the difference being indicative of at least two of the distributed computer control systems being out of synchronization by more than a threshold deviation.
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公开(公告)号：US11472452B2
公开(公告)日：2022-10-18
申请号：US16599830
申请日：2019-10-11
Applicant: PROGRESS RAIL SERVICES CORPORATION
Inventor： Bradley Howard , John Brand
Abstract: A train control system may include a data acquisition hub connected to a database and sensors associated with one or more locomotives, systems, or components of a train and configured to acquire data in association with inputs derived from contextual data relating to a plurality of trains being operated by experienced train engineers under a variety of different conditions and in different geographical areas for use as training data. A machine learning engine of the train control system may receive the training data from the data acquisition hub, encode a modified learning function as a statistical model of desirable train handling behavior, evaluate train handling behavior by comparing to the statistical model, and update a certification of one or more of a train engineer, a semi-autonomous control system, or a fully autonomous control system.
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公开(公告)号：US11447164B2
公开(公告)日：2022-09-20
申请号：US16599742
申请日：2019-10-11
Applicant: PROGRESS RAIL SERVICES CORPORATION
Inventor： Bradley Howard , John Brand
Abstract: A train control system uses artificial intelligence for maintaining synchronization between centralized and distributed train control models. A machine learning engine receives training data from a data acquisition hub, a first set of output control commands from a centralized virtual system modeling engine, and a second set of output control commands from a distributed virtual system modeling engine. The machine learning engine compares the first set of output control commands and the second set of output control commands, and trains a learning system using the training data to enable the machine learning engine to safely mitigate any difference between the first and second sets of output control commands using a learning function including at least one learning parameter.
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公开(公告)号：US11332173B2
公开(公告)日：2022-05-17
申请号：US16599807
申请日：2019-10-11
Applicant: PROGRESS RAIL SERVICES CORPORATION
Inventor： Bradley Howard , John Brand
Abstract: A train control system uses machine learning for implementing handovers between centralized and distributed train control models. A machine learning engine receives training data from a data acquisition hub, receives a centralized train control model from a centralized virtual system modeling engine, and receives an edge-based train control model from an edge-based virtual system modeling engine. The machine learning engine trains a learning system using the training data to enable the machine learning engine to predict when a locomotive of the train will enter a geo-fence where communication between the edge-based computer processing system and the centralized computer processing system will be inhibited.
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公开(公告)号：US11453421B2
公开(公告)日：2022-09-27
申请号：US16599855
申请日：2019-10-11
Applicant: PROGRESS RAIL SERVICES CORPORATION
Inventor： Bradley Howard , John Brand
Abstract: A system may include a data acquisition hub connected to databases and sensors associated with locomotives, systems, or components of a train and configured to acquire real-time and historical configuration, structural, and operational data in association with inputs derived from real time and historical contextual data relating to a plurality of trains. The system may include a virtual system modeling engine configured to receive results of a non-destructive evaluation of a train component, simulate in-train forces, determine a predicted time of failure for the train component based on an evaluation of stresses that have already been applied to the component and expected future stresses, and implement repair, replacement, or operational protocols for the train component before or at a repair facility that will be reached by the train ahead of a predetermined minimum threshold time period before the predicted time of failure.
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