A device is for detecting compaction and shear strength characteristics of an asphalt mixture during construction compaction. The device includes a fixed frame and a detection system. The detection system includes a display, a control panel, a test claw, an electric motor, a lift switch, a torque sensor and a temperature sensor. The control panel includes a power switch for controlling the electric motor and a speed regulator for controlling a rotation speed of the test claw. An output end of the electric motor is connected to an input end of the torque sensor, and an output end of the torque sensor is connected to an input end of the test claw. An output end of the test claw is provided with a claw-shaped blade. The claw-shaped blade is provided therein with the temperature sensor.

A device is for detecting compaction and shear strength characteristics of an asphalt mixture during construction compaction. The device includes a fixed frame and a detection system. The detection system includes a display, a control panel, a test claw, an electric motor, a lift switch, a torque sensor and a temperature sensor. The control panel includes a power switch for controlling the electric motor and a speed regulator for controlling a rotation speed of the test claw. An output end of the electric motor is connected to an input end of the torque sensor, and an output end of the torque sensor is connected to an input end of the test claw. An output end of the test claw is provided with a claw-shaped blade. The claw-shaped blade is provided therein with the temperature sensor.

A modular pavement slab comprises a body, a strain sensor array, and a sensor processor. The body includes a top surface, a bottom surface, and four side surfaces. The modular pavement slab is configured to be coupled to at least one other modular pavement slab via connectors along at least one of the side surfaces. The strain sensor array is retained within the body and is configured to detect a plurality of strains on the body resulting from vehicular traffic across the top surface of the body. The sensor processor is in communication with the strain sensor array. The sensor processor is configured to communicate input signals to the strain sensor array, receive output signals from the strain sensor array, and determine a plurality of time-varying strain values, each strain value indicating a strain experienced over time by a successive one of a plurality of regions of the body.

A paving machine includes a plurality of sensor(s) for generating sensor data associated with a paving operation. Criteria associated with paving mat defects are compared against the sensor data to determine whether the criteria is satisfied and whether paving mat defects are predicted. For example, criteria may include whether a hopper of the paving machine is activated, whether a screed assembly of the paving machine is floating, a speed of the paving machine, and whether heat is applied to the screed assembly. In instances where defects are predicted, notifications of such may be provided, or displayed, on a control interface of the paving machine.

A paving machine includes a plurality of sensor(s) for generating sensor data associated with a paving operation. Criteria associated with paving mat defects are compared against the sensor data to determine whether the criteria is satisfied and whether paving mat defects are predicted. For example, criteria may include whether a hopper of the paving machine is activated, whether a screed assembly of the paving machine is floating, a speed of the paving machine, and whether heat is applied to the screed assembly. In instances where defects are predicted, notifications of such may be provided, or displayed, on a control interface of the paving machine.

A road surface damage detection device is configured to calculate, for each of road sections, a maximum variation rate that is a maximum value of a variation amount of a wheel speed per unit time in each of vehicles. The device is configured to periodically select, for each of the road sections, a maximum value from the maximum variation rate of each of the vehicles in a prescribed period, set the selected maximum value as a section maximum variation rate, and determine whether or not the road surface damage has occurred by comparing a determination target value with a positive threshold, the determination target value being obtained by subtracting a comparison value, based on at least one of the section maximum variation rates set before last time, from the section maximum variation rate that is set latest.

A ground penetrating radar device and/or other sensor such as LIDAR, pressure, or temperature sensors is mounted on a mobile device, and is adapted, during motion of the mobile device, to sense characteristics of asphalt pavement on which the mobile device is moving, prior to compaction of the asphalt pavement by rollers. A processor, functionally associated with at least one sensor, receives from the sensor signals relating to characteristics of the asphalt pavement on which the mobile device is moving, and computes, based on the received signals, at least one compaction characteristic of the asphalt pavement. The processor provides a mapping of computed desired change in compaction characteristics to regions of the asphalt pavement during the rolling process. During rolling, at least one sensor measures the change in compaction and assesses when the change in compaction matches the desired optimal compaction based on the pre-generated map.

A method and system for estimating an unevenness parameter of a road segment having a length (L) are disclosed; the method and system take into account road unevenness induced vehicle body motions and are based on the estimation of the deformation, over multiple tire rotations, of at least two tires fitted to different axles of a vehicle.

A method and system for estimating an unevenness parameter of a road segment having a length (L) are disclosed; the method and system take into account road unevenness induced vehicle body motions and are based on the estimation of the deformation, over multiple tire rotations, of at least two tires fitted to different axles of a vehicle.

A device is provided for monitoring the compaction of concrete introduced into a slipform of a slipform paver by means of at least one concrete compacting device that has an asynchronous motor for driving an unbalanced mass which generates vibrations. The monitoring device comprises an apparatus for monitoring the stator current of the asynchronous motor, the apparatus being configured such that a change in the compaction of the concrete is determined based on an analysis of the stator current. The apparatus for monitoring the stator current of the asynchronous motor is preferably configured such that the amplitude spectrum of the stator current is determined in order to analyse the stator current. It is advantageous that the compaction of the concrete is not monitored using sensors which are exposed to harsh ambient conditions during operation of the slipform paver.