A structure displacement amount measurement apparatus includes: an acquiring unit configured to acquire a displacement amount caused on a structure by a weight of a vehicle traveling on the structure along a time series; an estimating unit configured to estimate a section in which displacement is caused based on time-series data of the displacement amount; a detecting unit configured to detect a feature value of change in displacement amount within the estimated section; a determining unit configured to determine whether or not the estimated section is a section of displacement due to a weight of a single vehicle based on the detected feature value; and an extracting unit configured to extract a displacement amount from the time-series data within a section of displacement due to a weight of a single vehicle based on a result of the determination.

Systems and methods for monitoring eye health. The systems and methods monitor eye health by measuring scleral strain by way of an implantable monitor, a wearable monitor configured in eyeglasses, or an external monitor using a portable tablet computing device. Certain embodiments of the strain monitor may be utilized to measure the strain on any surface to which it is attached, including, but not limited to, the skin of a patient or the surface of a structure such as a building or a bridge.

A bridge detecting vehicle with two foldable arms, including: a vehicle body, slewing mechanisms, horizontal and vertical arms and telescopic arms. One end of the two horizontal arms is respectively arranged on the slewing mechanisms, and the other end of the two horizontal arms is respectively connected to the two horizontal arms. A crossed arm is provided between the two horizontal arms. The two vertical arms are respectively connected to the two horizontal arms via ball joints. A detecting device is respectively provided at rear ends of the two telescopic arms.

A state detection apparatus includes a state detection sensor that is attached to an architecture and that detects a state of the architecture, a power supp that generates power on the basis of vibration of the architecture, and a controller that controls the state detection sensor and the power supp. The controller supplies power to the state detection sensor to drive the state detection sensor in a case where a voltage by power generation exceeds a first threshold (threshold voltage), and acquires state information to be used for diagnosing the state of the architecture on the basis of a signal indicating a detection result received from the state detection sensor.

Systems and methods for measuring the distance to a target object and acquiring scale and point-to-point distance information for that target object in an environment using a remotely operated flying platform, such as an unmanned aerial vehicle (UAV). The system uses on-board sensors and processing techniques to provide discrete or continuous measurements of the distances between points on a target object or the scale of the target object. The addition of on-board three-dimensional measurement capabilities to UAVs (or other flying platforms) allows the collection of distance data. Having this capability enables these systems to acquire distances between points on a single object, such as determining the true scale factors of items in images captured by the UAV, in the course of performing metrology-related tasks.

A sensor capable of monitoring the condition of a physical structure is provided. The sensor may be comprised of a plurality of flexible conductive segments arranged in a geometric pattern. The sensor also includes nodes within the geometric pattern. The sensor monitors the condition of a physical structure by monitoring the electrical resistance within the flexible conductive segments. Additional secondary sensors may also be included within the geometric pattern of the sensor. A processor may use the information from the flexible conductive segments and any secondary sensors to assess the condition of the physical structure.

A displacement component detection apparatus 10 is provided with: a displacement distribution calculation unit 11 configured to calculate, from time-series images of a measurement target region of an object 30 output from an image capturing device 20 configured to capture the images of the measurement target region, a displacement distribution in a region that corresponds to the measurement target region in the images; a movement amount calculation unit 12 configured to calculate, based on the displacement distribution and image capturing information, a movement amount in the surface direction of the measurement target region and a movement amount in the normal direction of the measurement target region; and a surface displacement calculation unit 13 configured to calculate, from the displacement distribution, a surface displacement component in the measurement target region, using the movement amount in the surface direction of the measurement target region and the movement amount in the normal direction of the measurement target region.

A degradation state determination apparatus 100 is an apparatus for determining the state of a structure, and includes a measurement unit 10 configured to measure a deflection amount and a surface displacement amount of the structure, a statistical processing unit 20 configured to executes statistical processing using the measured deflection amount and surface displacement amount, and a degradation state determination unit 30 configured to determine the degradation state of the structure based on the result of statistical processing.

A state determination apparatus 100 determines the state of a structure 200. The state determination apparatus 100 includes a measurement unit 10 configured to measure a deflection amount and a surface displacement amount in each of a plurality of target regions that are preset on the structure 200, a feature value calculation unit 20 configured to calculate, for the respective target regions, feature values each indicating a relationship between the deflection amount and the surface displacement amount, using the measured deflection amount and surface displacement amount, a spatial distribution calculation unit 30 configured to calculate a spatial distribution of the feature values using the feature values calculated for each of the target regions, and a degradation state determination unit 40 configured to determine a degradation state of the structure 200 based on the spatial distribution of the feature value.

A computer-vision-based fatigue crack detection approach using a short video is described. Feature tracking is applied to the video for tracking the surface motion of the monitored structure under repetitive load. Then, a crack detection and localization algorithm is established to search for differential features at different frames in the video. The effectiveness of the proposed approach is validated through testing two experimental specimens with in-plane and out-of-plane fatigue cracks. Results indicate that the proposed approach can robustly identify fatigue cracks, even when the cracks are under ambient lighting conditions, surrounded by other crack-like edges, covered by complex surface textures, or invisible to human eyes due to crack closure. The approach enables accurate quantification of crack openings under fatigue loading with good accuracy.