This disclosure relates to the inspection of train wheels while mounted on a train that is moving on a railroad track. A magnetostrictive EMAT transducer is built using an RF Coil, a static biasing magnetic field, and a strip of highly magnetostrictive material. This magnetostrictive EMAT transducer is subsequently attached to a rail on the track so the wheel tread of the moving train can contact and apply downward pressure on the magnetostrictive EMAT transducer. A mechanism under the transducer provides enough counterforce to pressure-couple the transducer with the tread of the wheel. Once the transducer is ultrasonically coupled with the wheel, an ultrasonic instrument sends a pulse to the transducer generating a Shear Horizontal wave that travels circumferentially following the tread body. The Shear Horizontal wave generated with this magnetostrictive strip EMAT transducer penetrates deep into the wheel tread and permits detection of both surface and internal defects.

This disclosure relates to the inspection of train wheels while mounted on a train that is moving on a railroad track. A magnetostrictive EMAT transducer is built using an RF Coil, a static biasing magnetic field, and a strip of highly magnetostrictive material. This magnetostrictive EMAT transducer is subsequently attached to a rail on the track so the wheel tread of the moving train can contact and apply downward pressure on the magnetostrictive EMAT transducer. A mechanism under the transducer provides enough counterforce to pressure-couple the transducer with the tread of the wheel. Once the transducer is ultrasonically coupled with the wheel, an ultrasonic instrument sends a pulse to the transducer generating a Shear Horizontal wave that travels circumferentially following the tread body. The Shear Horizontal wave generated with this magnetostrictive strip EMAT transducer penetrates deep into the wheel tread and permits detection of both surface and internal defects.

This application relates to an overload and unbalanced load detecting system for a railway and a detecting method. This system includes at least one steel rail. A rail web of each steel rail is provided with two sampling points at two sides between every two adjacent rail sleepers, respectively, and the two sampling points on one side are symmetrically disposed about the steel rail with respect to the two sampling points on the other side. A fiber-optic sensitive element used for continuously measuring a load when a train passes through the two sampling points is obliquely fixed at each sampling point, and two fiber-optic sensitive elements on the same side of each steel rail are disposed at an angle of 90 with each other.

A system continuously monitors bearing temperature and wheel surface condition. The system may include a button contact sensor for sensing wheel bearing temperature and a measuring laser for detecting wheel breakage. The system may also include a vibration sensor, sound sensor, and a load sensor. Each sensor is in communication with a receiver/transmitter and may be mounted to the railcar by way of a friction lock magnetic mounting. Computer means may be used to store, analyze, and present the collected information for use in deciding whether, for example, the train should be slowed or stopped. A solar panel may provide power to the components.

A system continuously monitors bearing temperature and wheel surface condition. The system may include a button contact sensor for sensing wheel bearing temperature and a measuring laser for detecting wheel breakage. The system may also include a vibration sensor, sound sensor, and a load sensor. Each sensor is in communication with a receiver/transmitter and may be mounted to the railcar by way of a friction lock magnetic mounting. Computer means may be used to store, analyze, and present the collected information for use in deciding whether, for example, the train should be slowed or stopped. A solar panel may provide power to the components.

A measurement process, intended for measuring at least one wheel of a train, including an acquisition step, during which a plurality of profiles of at least a part of the wheel are acquired by plurality of optical sensors, as the train moves in front of the optical sensors, a mapping step, during which, for each optical sensor, the profiles acquired by the optical sensor are joined by a control module, to obtain a map of the part of the wheel further transformed into a cloud of points, a rejoining step, during which the clouds of points obtained from the optical sensors are joined to form a three-dimensional image of the wheel, and an analysis step, during which a plurality of reference points and reference distances are measured on the three-dimensional image.

A measurement process, intended for measuring at least one wheel of a train, including an acquisition step, during which a plurality of profiles of at least a part of the wheel are acquired by plurality of optical sensors, as the train moves in front of the optical sensors, a mapping step, during which, for each optical sensor, the profiles acquired by the optical sensor are joined by a control module, to obtain a map of the part of the wheel further transformed into a cloud of points, a rejoining step, during which the clouds of points obtained from the optical sensors are joined to form a three-dimensional image of the wheel, and an analysis step, during which a plurality of reference points and reference distances are measured on the three-dimensional image.

An evaluation unit is fed with driving-related diagnostic data of a reference railway vehicle. The diagnostic data contain driving-related properties, on which a parameter of the wheel of the reference railway vehicle depends. The evaluation unit is also fed with wheel measurement data with measured values of the parameter of the wheel of the reference railway vehicle. The evaluation unit determines a function between the driving-related diagnostic data and the wheel measurement data via a supervised learning algorithm. The evaluation unit is fed with driving-related diagnostic data containing driving-related properties of an observed railway vehicle, on which a parameter of the wheel of the observed railway vehicle depends. The parameter of the wheel of the observed railway vehicle is determined by the evaluation unit using the determined function and the diagnostic data of the observed railway vehicle.

An evaluation unit is fed with driving-related diagnostic data of a reference railway vehicle. The diagnostic data contain driving-related properties, on which a parameter of the wheel of the reference railway vehicle depends. The evaluation unit is also fed with wheel measurement data with measured values of the parameter of the wheel of the reference railway vehicle. The evaluation unit determines a function between the driving-related diagnostic data and the wheel measurement data via a supervised learning algorithm. The evaluation unit is fed with driving-related diagnostic data containing driving-related properties of an observed railway vehicle, on which a parameter of the wheel of the observed railway vehicle depends. The parameter of the wheel of the observed railway vehicle is determined by the evaluation unit using the determined function and the diagnostic data of the observed railway vehicle.

In one aspect, a mobile railway asset monitoring apparatus is provided that includes a sensor configured to produce a signal indicative of a rotation of a wheelset of a mobile railway asset. The apparatus further includes a processor to receive data corresponding to a ground speed of the mobile railway asset. The processor is operably coupled to the sensor, the processor configured to estimate a running dimension of the wheelset based at least in part on the rotation of the wheelset and the ground speed of the mobile railway asset. The processor is configured to determine at least one parameter of the mobile railway asset based at least in part on the running dimension of the wheelset.