Provided is a technology of estimating a bending stiffness variation of a tire and estimating a tread wear amount of a tire using the same. A tire wear measuring apparatus wear includes a signal receiver configured to measure acceleration inside the tire with respect to an axial direction, which is a radial direction of the tire, for each point inside the tire, a signal analyzer configured to receive signal information from the signal receiver and estimate a tread wear rate of the tire by calculating a bending stiffness variation rate of the tire using axial acceleration inside the tire, a transmitter configured to receive and transmit analysis information, which is information on the tread wear rate of the tire, from the signal analyzer, and a control module configured to receive the analysis information from the transmitter and generate a control signal for a vehicle to which the tire is installed. Meanwhile, a physical change thereof is derived using a Flexible Ring tire model which is a mathematical model.

A method and system are provided for estimating tire tread depth, the method comprising: obtaining an image of the tire informative of tread and grooves embedded therein, wherein the image is acquired by an imaging device from a first angle relative to a horizontal direction perpendicular to tread surface, and the tire is illuminated by an illumination device from a second angle relative to the horizontal direction, causing a shadow section and an illuminated section at the bottom and/or sidewall of a groove, the first angle being smaller than the second angle, such that the image captures the illuminated section and at least part of the shadow section; performing segmentation on the image to obtain image segments corresponding to the illuminated section and the at least part of the shadow section; and estimating the tread depth based on the image segments, the groove width, and the second angle.

This disclosure provides a tire formed of a body having multiple plies and a tread that surrounds the body. In some implementations, the plies and/or the tread include a resonator that generates a resonant signal in response to being activated by locally generated power or by an externally generated excitation signal. Multiple resonators formed of carbon-containing materials are distributed in the plies and/or tread to respond to changes to the tire by altering a characteristic of the resonant signal. Such alterations include frequency shifting of the resonant signal and/or attenuation of the resonant signal. The resonator can be configured to resonate at a first frequency when a structural characteristic of a respective ply or tread is greater than a level, and to resonate at a second frequency different than the first frequency when the structural characteristic of the respective ply or tread is not greater than the level.

An automated tread analysis system and methods for using are described. The automated tread analysis system may include a sensing system having a plurality of cameras providing a plurality of sequential two-dimensional images. The automated tread analysis system may also include an analysis system configured to provide at least one surface model of a first object via photogrammetry using the plurality of sequential two-dimensional images. The automated tread system may execute processing software reading data corresponding to the at least one surface model of the first object. The surface model may correspond to a current condition of the first object. The processing software executed by the user system may analyze the at least one surface model of the first object and provide at least one indicative wear metric based on the analysis of the surface model of the first object.

The invention concerns a tread wear monitoring method comprising a tread wear model calibration step (1) and a tread wear monitoring step (2), wherein the tread wear model calibration step (1) includes determining (13) a calibrated tread wear model based on tread-wear-related quantities and first frictional-energy-related quantities. The tread wear monitoring step (2) includes: acquiring (21), from a vehicle bus (40) of a motor vehicle (4) equipped with two or more wheels fitted, each, with a tire, driving-related quantities related to driving of the motor vehicle (4); computing (22) second frictional-energy-related quantities related to frictional energy experienced, during driving, by a given tire of the motor vehicle (4) by providing a predefined vehicle dynamics model that mathematically relates the acquired driving-related quantities to the second frictional-energy-related quantities, and computing the second frictional-energy-related quantities by inputting the acquired driving-related quantities into the predefined vehicle dynamics model; and performing a tread wear estimation (23) and a remaining tread material prediction (24) based on the second frictional-energy-related quantities computed and the calibrated tread wear model. The tread wear model calibration step (1) further includes: performing (11) tread wear tests on one or more tires; and measuring (12) tread-wear-related quantities indicative of tread depth reductions resulting from the performed tread wear tests, and first frictional-energy-related quantities related to frictional energy which the tested tire(s) is/are subject to during the performed tread wear tests. Determining (13) a calibrated tread wear model includes: providing a predefined reference tread wear model that mathematically relates frictional energy experienced by a tire along a driving route to tread wear caused by said frictional energy through given parameters; computing calibration values of the given parameters by inputting the measured tread-wear-related and first frictional-energy-related quantities into the predefined reference tread wear model; and determining the calibrated tread wear model by applying the computed calibration values in the predefined reference tread wear model.

The invention concerns a tread wear monitoring method comprising a preliminary step (6) and a tread wear monitoring step (7). The preliminary step (6) includes: performing tread wear tests on one or more tires; measuring tread-wear-related quantities and first frictional-energy-related quantities, wherein the tread wear-related quantities are indicative of tread wear resulting from the performed tread wear tests, and the first frictional-energy-related quantities are related to frictional energy which the tested tire(s) is/are subject to during the performed tread wear tests; and determining a calibrated tread wear model based on the measured tread-wear-related and first frictional-energy-related quantities. The tread wear monitoring step (7) includes: acquiring, from a vehicle bus (40) of a motor vehicle (4) equipped with two or more wheels fitted, each, with a tire, driving-related quantities related to driving of the motor vehicle (4); computing, based on the acquired driving-related quantities and a predefined vehicle dynamics model related to the motor vehicle (4), second frictional-energy-related quantities related to frictional energy experienced, during driving, by at least one tire of the motor vehicle (4); estimating, based on the second frictional-energy-related quantities and the calibrated tread wear model, tread wear experienced by said at least one tire of the motor vehicle (4) during driving; and estimating a current average remaining tread material amount of said at least one tire of the motor vehicle (4) based on the estimated tread wear. Additionally, the preliminary step (6) further includes: determining, based on one or more of the measured tread-wear-related quantities, a first correction factor related to irregular tread wear due to tire features; and training an artificial neural network to provide second correction factors related to irregular tread wear due to tire usage. Finally, the tread wear monitoring step (7) further includes: providing a second correction factor by means of the trained artificial neural network based on one or more of the acquired driving-related quantities; and computing a corrected remaining tread material amount based on the current average remaining tread material amount, the first correction factor and the second correction factor provided by the trained artificial neural network based on the one or more acquired driving-related quantities.

A remaining tire tread depth management system includes a remaining tire tread depth measurement device configured to measure a remaining tread depth of at least one of aircraft tires mounted on an aircraft, a tire wear amount estimation device configured to estimate a wear amount of all of the aircraft tires mounted on the aircraft including the aircraft tires, and a tire management server configured to estimate a remaining tread depth and a number of available flight times of all of the aircraft tires in accordance with measurement data output from the remaining tire tread depth measurement device and estimation data output from the tire wear amount estimation device.

An at least one acoustic sensor in form of a microphone configured for coupling with a tire pressure monitoring system and tire pressure monitoring system unit sensor to generally detect an acoustic signal within a tire interior space generated by a tire as the tire travels across a road surface. The detected signal can be used by various vehicle systems to generally determine a tire condition, such as, but not limited to, tread wear, tread depth, tire health, road condition, road characterization, status of noise reducing foam, and active noise cancelling.

A management system for tires for construction and mine vehicles comprises: a fatigue degree calculation section; a grouping processing section configured to group a plurality of front tires into a plurality of fatigue degree groups depending on calculated fatigue degrees; and an assignment processing section configured to assign front tires belonging to a fatigue degree group as rear tires of a vehicle after rotation. A management method for tires for construction and mine vehicles comprises: a fatigue degree calculation step; a grouping step of grouping a plurality of front tires into a plurality of fatigue degree groups depending on calculated fatigue degrees; and an assignment step of assigning front tires belonging to a fatigue degree group as rear tires of a vehicle after rotation.

A method of detecting degradation of a real tire of a wheel includes the steps of: acquiring at least one first three-dimensional object representative of the shape of the real tire by using an electronic appliance including at least one three-dimensional sensor, the first three-dimensional object being made up of a set of capture points; determining the position of the center point of the real tire from the set of capture points; registering the first three-dimensional object to obtain a second three-dimensional object; transforming the second three-dimensional object in order to obtain one or more two-dimensional objects; and analyzing the two-dimensional object(s) in order to detect degradation of the real tire.