A method and device for compacting the ballast bed of a track, especially in the region of a switch, comprising a switch tamping machine (1), which is fitted with a tamping unit (4), a lifting and lining device (2) comprising at least one pair of roller pincers (6) and at least one lifting hook (7) for lining the track position, and which is guided in a longitudinally displaceable manner on the machine frame (2) in the longitudinal direction of the machine. In order to provide advantageous lining conditions, it is proposed that a switch component measuring system (3), which is provided upstream of the lifting and lining device (2) in the working direction (C), is provided for the position-dependent measurement of the position of the switch components.

A method and device for compacting the ballast bed of a track, especially in the region of a switch, comprising a switch tamping machine (1), which is fitted with a tamping unit (4), a lifting and lining device (2) comprising at least one pair of roller pincers (6) and at least one lifting hook (7) for lining the track position, and which is guided in a longitudinally displaceable manner on the machine frame (2) in the longitudinal direction of the machine. In order to provide advantageous lining conditions, it is proposed that a switch component measuring system (3), which is provided upstream of the lifting and lining device (2) in the working direction (C), is provided for the position-dependent measurement of the position of the switch components.

An aspect includes a vehicle that includes rail inspection sensors configured for capturing transducer data describing the rail, and a processor configured for receiving and processing the transducer data in near-real time to determine whether the captured transducer data identifies a suspected rail flaw. The processing includes inputting the captured transducer data to a machine learning system that has been trained to identify patterns in transducer data that indicate rail flaws. The processing also includes receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw. An alert is transmitted to an operator of the vehicle based at least in part on the output indicating that the captured transducer data identifies a suspected rail flaw. The alert includes a location of the suspected rail flaw and instructs the operator to stop the vehicle and to perform a repair action.

An aspect includes a vehicle that includes rail inspection sensors configured for capturing transducer data describing the rail, and a processor configured for receiving and processing the transducer data in near-real time to determine whether the captured transducer data identifies a suspected rail flaw. The processing includes inputting the captured transducer data to a machine learning system that has been trained to identify patterns in transducer data that indicate rail flaws. The processing also includes receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw. An alert is transmitted to an operator of the vehicle based at least in part on the output indicating that the captured transducer data identifies a suspected rail flaw. The alert includes a location of the suspected rail flaw and instructs the operator to stop the vehicle and to perform a repair action.

A track maintenance machine, with a sensor for identifying an A-point of a chord, having a frame, axles, and wheels operatively connected to the axles and configured to support the machine on a track. A workhead is arranged between the axles. A B-point is placed at the workhead at a predetermined height above the track, and a C-point placed at a rear end of the at a predetermined height above the track. A sensor is arranged at a forward end of the frame at a predetermined height above the track. The sensor scans forward of the machine to identify an A-point; acquire track data for the A-point; and transmit the data to a machine control system. The machine control system is configured to calculate a chord by combining the track data for the A-point with the C-point to calculate operation data for the workhead at the B-point.

A track maintenance machine, with a sensor for identifying an A-point of a chord, having a frame, axles, and wheels operatively connected to the axles and configured to support the machine on a track. A workhead is arranged between the axles. A B-point is placed at the workhead at a predetermined height above the track, and a C-point placed at a rear end of the at a predetermined height above the track. A sensor is arranged at a forward end of the frame at a predetermined height above the track. The sensor scans forward of the machine to identify an A-point; acquire track data for the A-point; and transmit the data to a machine control system. The machine control system is configured to calculate a chord by combining the track data for the A-point with the C-point to calculate operation data for the workhead at the B-point.

A device for monitoring wear of a flange (1) of a roller (2) includes a peripheral rim (3) and intended to cooperate with a homologous flange (1bis) of a roller (2bis) positioned face-to-face to interact with the head of a rolling rail (4). The device includes at least one first recess localized at the level of a peripheral line of constant radius on the flange (1) configured to be positioned at the level at which the point (7) of separation of the flange (1) relative to its homologue (1bis) is the smallest.

A device for monitoring wear of a flange (1) of a roller (2) includes a peripheral rim (3) and intended to cooperate with a homologous flange (1bis) of a roller (2bis) positioned face-to-face to interact with the head of a rolling rail (4). The device includes at least one first recess localized at the level of a peripheral line of constant radius on the flange (1) configured to be positioned at the level at which the point (7) of separation of the flange (1) relative to its homologue (1bis) is the smallest.

Systems and methods for a first rail grinding machine and a second rail grinding machine can be used to enhance specialized rail grinding. A first rail grinding machine can detect, process, and communicate a portion of track rail needing specialized grinding to a second rail grinding machine that can process and display a detected portion of rail requiring specialized rail grinding and display the portion of rail as a virtual image to an operator. A displayable image allows an operator to perform specialty rail grinding without the need to be physically present at the location for specialized rail grinding.

This disclosure relates generally to systems and methods for data acquisition and asset inspection in presence of magnetic interference. Data acquisition and assets inspection systems in many infrastructures such as railway, power line, and bridges provide inaccurate results in presence of magnetic interference. The proposed system and method proposes UAV based navigation through a dynamic correction path to inspect one or more assets in one or more infrastructures. A plurality of sensors are integrated with the UAV to acquire images of the one or more assets in presence of magnetic field. The acquired images are further processed to segment and detect anomalies in one or more parts of the one or more assets. The detected anomalies are further classified as potential anomalies and non-potential anomalies. The proposed method provides accurate results with reduced processing time.