A state estimation apparatus 1 includes an acquisition unit 2 that acquires deterioration information indicating a deterioration state of each structural object and a learning unit 3 that learns common information that is common between pieces of the deterioration information and estimation index information that is used for estimating a deterioration state of a target structural object, using the deterioration information as input.

Disclosed herein is a method for monitoring a health status of one or of a plurality of bridges (10) under normal traffic condition. The method comprises: a) providing at least one sensing device (12) per bridge configured to measure a physical quantity variation related to the integrity of said one or said plurality of bridges; b) providing a fleet of heavy vehicles (14), wherein an estimation of the weight of each heavy vehicle is known with a deviation of no more than 10% of the actual weight of each heavy vehicle; c) acquiring a set of physical data related to the integrity of said one or said plurality of bridges (10) from said at least one sensing device (12) when at least one heavy vehicle of the fleet crosses one bridge (10); d) determining the configuration of other vehicles (15a, 15b, 15c, 15d, 15e) on the bridge, if any, when said at least one heavy vehicle (14) crosses said one bridge; e) repeating steps c) and d) in order to acquire multiple sets of physical data related to the integrity of said one or said plurality of bridges (10) so that the number of sets of integrity data associated with one bridge (10) permits to measure or observe a deviation, and c) obtaining a health status of said one or said plurality of bridges based on the deviation between said multiple sets of physical data associated with one bridge.

A device for fatigue test includes a sample-laying part, a sample support, and a force-applying part. The sample-laying part is disposed on the sample support; and the force-applying part is disposed on the sample-laying part; the sample-laying part includes a substrate plate and at least two arms disposed on the substrate plate; the sample support includes a bed plate and at least four roller assemblies disposed on the bed plate; each roller assembly includes a roller, a roller support, and an adjusting bolt; the roller support is disposed on the bed plate; the roller is disposed on the roller support; the adjusting bolt is disposed between the roller and the roller support; and the sample support further includes at least one barrier, and both ends of the barrier are connected to two adjacent roller supports, respectively.

A method for identifying prestress force in single-span or multi-span PCI girder-bridges is provided. The method includes non-destructive steps for obtaining a set of parameters of the PCI girder-bridge under investigation, and combines various analyses to identify the change of prestress force. Therefore, the losses of prestress force are tracked and predicted. The method does not cause structural damages along the PCI girder-bridge, and the cost of the identification is significantly decreased.

The disclosure provides a method for identifying a modal frequency of a beam bridge by considering influence of environmental temperature. The method includes the following steps: installing a sensor on a newly-built beam bridge without damage, measuring a dynamic response of the nearn bridge cinder ambient excitation, recording temperature data, processing by a modal parameter identification method to obtain a modal frequency value at the temperature, and titarling from a modal frequency corresponding to the temperature, carrying out iterative calculation to obtain the modal frequency at any temperature. The modal frequency value at any temperature is obtained by arranging a small number of sensors and canying out a small number of tests, so that the influence of the temperature on the modal frequency is quantified, furthermore, the part of environmental influence is eliminated in future damage evaluation of the beam bridge, which allows for a more accurate isamage evaluation rttsult,

A drone system for collecting structural condition data about a structure having an array of sensors disposed at various locations on the structure and methods of using such a drone system are disclosed herein. The drone inspection system leverages neural networks to calculate a drone flight path to classify the location of passive sensors and calculate a drone flight path to collect structural condition data about the structure using line of sight sensors for digital twin generation. Some of the sensors disposed on the structure may be passive sensors that comprise energy harvesters and must be energized to report the structural collection data to the drone. The drone inspection system may comprise an energy transfer module for energizing the passive sensor via the energy harvester.

Provided are a structure inspection method and a structure inspection system capable of easily detecting an abnormal location and inspecting an internal state of the abnormal location in detail. The structure inspection method includes: a step of capturing a thermal image of a surface of a structure with an infrared camera; a step of detecting a first region estimated to have an internal abnormality, on the basis of the thermal image; and a step of measuring an internal state of the first region in a case where the first region is detected. In the step of measuring the internal state of the first region, the internal state of the first region is measured by capturing an image that visualizes the internal state of the first region using an electromagnetic wave or an ultrasonic wave.

Systems and methods include reception, for each of a first plurality of consecutive time periods, of an acceleration value associated with a first location of a structure, determination of a first value of a first indicator based on absolute values of the acceleration values, determination of a second value of a second indicator based on absolute values of differences of consecutive one of the acceleration values, determination of a first value of an index based on the first value and the second value, determination of a physical characteristic of the structure based on the first value of the first indicator and the first value of the index, and transmission of an alert based on the physical characteristic.

A system, apparatus, and method for remotely detecting defects in a structure may proceed non-destructively. A mobile sensing platform may place sensors in a desired positioning relative to the structure. The desired position may include a non-contacting relation between the sensors and structure. The mobile sensing platform may project laser beams onto the structure and sense backscattered light via the sensors. Variations in the backscattered light may correspond to motion of the structure, such as vibrations. By calculating the frequency and amplitude of the vibrations, defects in the structure may be detected. By correcting for noise, such as that associated with acceleration of the mobile sensing platform, accuracy and precision of defect detection may be enhanced.

In a method of estimating displacement of a bridge, a first displacement including a low frequency component and a first high frequency component is generated based on a strain that is measured by a plurality of pairs of strain gauges installed at positions in a first direction from a reference point, in a bridge, a second displacement including a second high frequency component is generated based on an acceleration that is measured by an accelerometer installed at a first position spaced apart from the reference point by a first distance in the first direction, in the bridge, and a final displacement of the bride is generated based on an unknown parameter associated with the displacement, the low frequency component and the second high frequency component. The unknown parameter is generated by applying a recursive least square algorithm to the first high frequency component and the second high frequency component.