A method of determining a road surface condition includes: acquiring, when determining a condition of a road surface being in contact with a tire from a time-varying waveform of vibration of the running tire, the time-varying waveform of vibration having been detected by a vibration detecting means, a plurality of intrinsic vibration modes, from data of the time-varying waveform of vibration of the tire, using an algorithm of empirical mode decomposition; selecting an arbitrary intrinsic vibration mode from the plurality of intrinsic vibration modes; calculating a statistic amount from the distribution of feature data calculated by performing Hilbert transform on the selected intrinsic vibration mode to set the statistic amount as a feature amount; and determining the road surface condition from the feature amount and a feature amount obtained in advance for each road surface condition.

A method of determining a road surface condition includes: acquiring, when determining a condition of a road surface being in contact with a tire from a time-varying waveform of vibration of the running tire, the time-varying waveform of vibration having been detected by a vibration detecting means, a plurality of intrinsic vibration modes, from data of the time-varying waveform of vibration of the tire, using an algorithm of empirical mode decomposition; selecting an arbitrary intrinsic vibration mode from the plurality of intrinsic vibration modes; calculating a statistic amount from the distribution of feature data calculated by performing Hilbert transform on the selected intrinsic vibration mode to set the statistic amount as a feature amount; and determining the road surface condition from the feature amount and a feature amount obtained in advance for each road surface condition.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

Systems, methods, and apparatus for tracking location of an inspection robot are disclosed. An example apparatus for tracking inspection data may include an inspection chassis having a plurality of inspection sensors configured to interrogate an inspection surface, a first drive module and a second drive module, both coupled to the inspection chassis. The first and second drive module may each include a passive encoder wheel and a non-contact sensor positioned in proximity to the passive encoder wheel, wherein the non-contact sensor provides a movement value corresponding to the first passive encoder wheel. An inspection position circuit may determine a relative position of the inspection chassis in response to the movement values from the first and second drive modules.

Systems, methods, and apparatus for tracking location of an inspection robot are disclosed. An example apparatus for tracking inspection data may include an inspection chassis having a plurality of inspection sensors configured to interrogate an inspection surface, a first drive module and a second drive module, both coupled to the inspection chassis. The first and second drive module may each include a passive encoder wheel and a non-contact sensor positioned in proximity to the passive encoder wheel, wherein the non-contact sensor provides a movement value corresponding to the first passive encoder wheel. An inspection position circuit may determine a relative position of the inspection chassis in response to the movement values from the first and second drive modules.

Methods and systems for determining the integrity of a manufactured board are disclosed. An example system includes a testing platform configured to secure the manufactured board, a sensor configured to measure a parameter corresponding to a flatness of a surface of the board, and a controller. The controller is configured to identify regions on the surface corresponding to one of a peak or a valley based on the parameter, and calculate a score representing the integrity of the manufactured board based on the identified peaks and valleys. The controller adjusts a flow rate, a pressure, a temperature, and position of a deposited substance in a manufacturing process based on a comparison with a height of the peak and/or a depth of the valley to stored peak heights and/or valley depths. In some examples, a mechanical tester determines a compressive strength and a density of the board at the identified regions.

Methods and systems for determining the integrity of a manufactured board are disclosed. An example system includes a testing platform configured to secure the manufactured board, a sensor configured to measure a parameter corresponding to a flatness of a surface of the board, and a controller. The controller is configured to identify regions on the surface corresponding to one of a peak or a valley based on the parameter, and calculate a score representing the integrity of the manufactured board based on the identified peaks and valleys. The controller adjusts a flow rate, a pressure, a temperature, and position of a deposited substance in a manufacturing process based on a comparison with a height of the peak and/or a depth of the valley to stored peak heights and/or valley depths. In some examples, a mechanical tester determines a compressive strength and a density of the board at the identified regions.

An inspection robot incudes a robot body, at least two sensors, a drive module, a stability assist device and an actuator. The at least two sensors are positioned to interrogate an inspection surface and are communicatively coupled to the robot body. The drive module includes at least two wheels that engage the inspection surface. The drive module is coupled to the robot body. The stability assist device is coupled to at least one of the robot body or the drive module. The actuator is coupled to the stability assist device at a first end, and coupled to one of the drive module or the robot body at a second end. The actuator is structured to selectively move the stability assist device between a first position and a second position. The first position includes a stored position. The second position includes a deployed position.

An inspection robot incudes a robot body, at least two sensors, a drive module, a stability assist device and an actuator. The at least two sensors are positioned to interrogate an inspection surface and are communicatively coupled to the robot body. The drive module includes at least two wheels that engage the inspection surface. The drive module is coupled to the robot body. The stability assist device is coupled to at least one of the robot body or the drive module. The actuator is coupled to the stability assist device at a first end, and coupled to one of the drive module or the robot body at a second end. The actuator is structured to selectively move the stability assist device between a first position and a second position. The first position includes a stored position. The second position includes a deployed position.

A surface texture measuring device according to the present invention includes a surface texture detecting component that outputs measurement results for a surface texture of a measurable object, where the measurement results are recognized as a change in the movement of a contact pin of a detector when tracing a surface of the measurable object with the contact pin; a posture detecting sensor that detects a measured posture, which is a posture at the time of measurement by the detector; a memory component that is preloaded with correction values corresponding to each of a plurality of postures; and a correcting component that compares the measured posture with the plurality of postures stored in the memory component, and corrects the measurement results using a correction value that corresponds to a posture equivalent to the measured posture.