In the system, two ultrasonic transducers, which form a pair and each have a piezoelectric ceramic plate-shaped element with a rectangular geometry, can be fastened to a surface of a component. The two ultrasonic transducers are arranged at a distance from one another such that there is no direct mechanical contact and they are arranged beside one another with a parallel orientation of their central longitudinal axes. The two elements have a different polarization along their width and are connected with the same polarity to an electrical voltage source. The two plate-shaped elements can also have an identical polarization along their width and can be connected in this case with opposite polarity to an electrical voltage source. At least one ultrasonic transducer and/or at least one further ultrasonic transducer is/are designed to detect ultrasonic waves reflected by defects and/or shear waves simultaneously emitted by the two ultrasonic transducers.

A system includes a sensor comprising a sensor bonding layer disposed on a surface of the sensor, wherein the sensor bonding layer is a metallic alloy. An inlay includes a planar outer surface, wherein the inlay may be disposed on a curved surface of a structure. A structure bonding layer may be disposed on the planar outer surface of the inlay, wherein the structure bonding layer is a metallic alloy. The sensor bonding layer is coupled to the structure bonding layer via a metallic joint, and the sensor is configured to sense data of the structure through the metallic joint, the structure bonding layer, and the sensor bonding layer. The inlay comprises at least one of a modulus of elasticity, a shape, a thickness, and a size configured to reduce strain transmitted to the sensor.

Provided is a sensor system which can detect a thickness reduction, a crack, or the like of a pipe or a container covered with a thick coating member through ultrasonic inspection without attachment and detachment of the coating member. A sensor system used for nondestructive inspection includes a sensor attached to a surface of an inspection target, a sensor coil that is electrically connected to the sensor via a first cable, a first electromagnetic wave blocking member that is disposed between the surface of the inspection target and the sensor coil, a sensor side coil that is disposed to face the sensor coil with a gap and is coupled to the sensor coil through electromagnetic induction, and a probe side coil that is disposed to be separated from the sensor side coil and is electrically connected to the sensor side coil via a second cable.

Structural health monitoring (SHM)/nondestructive evaluation (NDE) exists as a tool in conjunction with manufactured pieces. Presently disclosed subject matter integrates automated video with a structural health monitoring system. In conjunction with bridge monitoring, integration of such two systems automates determination of the effect or correlation of vehicular loading on SHM data from a subject bridge. Such correlations help to understand the sources of structural health monitoring data, particularly acoustic emission data, in bridges and other structures, such as dams and nuclear plants. Automation of the evaluation of bridges and other structures increases accuracy and minimizes risk to workers and the public. Assessing the structural condition of bridges and other structures as presently disclosed also facilitates automated asset management of transportation systems, such as by state departments of transportation and other bridge/structural owners.

A system includes a structure bonding layer and a sensor. The structure bonding layer is disposed on a structure. The structure bonding layer is a metallic alloy. The sensor includes a non-metallic wafer and a sensor bonding layer disposed on a surface of the non-metallic wafer. The sensor bonding layer is a metallic alloy. The sensor bonding layer is coupled to the structure bonding layer via a metallic joint, and the sensor is configured to sense data of the structure through the metallic joint, the structure bonding layer, and the sensor bonding layer.

The invention relates to a device for detecting faults of a structure (STR), the device comprising a calculation unit and a plurality of transducers (100) intended to be positioned on or in the structure (STR), first transducers (E) of the plurality de transducers (100) being capable of being in an emission mode, second transducers (R) of the plurality of transducers (100) being capable of being in a reception mode,
characterized in that the first transducers (E) form a hexagonal meshing so as to delimit between them several mutually adjacent mesh cells, the second transducers (R) being positioned on respective emission circles of the first transducers (E), each emission circle of a first transducer (E) being centered on the first transducer (E).

A sensor having one or more stopbands and method of using the same for detecting damage, cracking and debonding in a cement structure comprising a cementitious material and a plurality of periodic structures located in the cementitious material.

Systems and methods relate to testing and/or monitoring acoustic emissions detected at composite structures, such as carbon fiber structures, intended for use in extreme conditions, such as in high pressure conditions, high or low temperature conditions, conditions in which the composite structure is subjected to mechanical impacts, or the like. The systems and protocols are suitable for use with composite structures comprising, e.g., carbon fiber structures, such as hollow or partially hollow structures used in submersible vehicles, spacecraft, gas-fillable storage containers, pressure vessels, and the like, that are subjected to extreme conditions during use. Systems and methods disclosed herein are directed to collecting and analyzing data, determining background conditions, differentiating and classifying signals, conditioning or curing a material or structure, assessing, rating and/or validating the “health” of a material or structure in real-time, determining alarm conditions, predicting failure conditions, and the like.

A method for automatic determination of trends in the graphic analysis of turbomachinery, characterized by understanding the steps of: a) obtaining valid data from sensors installed on the turbomachinery for analysis; b) applying fourth order polynomial regression and evaluating its correlation with the sample; c) calculating the relative variation between the first and last points of the series; d) assessing whether the levels of relative variation and relative correlation exceed a previously pre-established minimum level; d1) displaying a non-existent trend result, if the relative variation or the relative correlation does not exceed the minimum level previously established; e) calculating the trend using the weighted average calculations; f) calculating and classifying the rate of change between consecutive values in the valid data series; g) determining parameters for the rate of change; h) checking if the rate of change parameters meet trend criteria, where: h1) if the rate of change parameters meet trend criteria, checking if the relative change is positive, where: h11) if the change relative is positive, displays a positive trend result; and h12) if the relative variation is negative, displays a negative trend result, h2) if the rate of change parameters do not meet trend criteria, checking if the relative variation is positive, where: h21) if the relative variation is negative, shows a result that there is a negative threshold change; and h22) if the relative variation is positive, displays a result that there is a positive threshold change, i) informing the results obtained; and j) taking corrective actions.

Structural health monitoring (SHM)/nondestructive evaluation (NDE) exists as a tool in conjunction with manufactured pieces. Presently disclosed subject matter integrates automated video with a structural health monitoring system. In conjunction with bridge monitoring, integration of such two systems automates determination of the effect or correlation of vehicular loading on SHM data from a subject bridge. Such correlations help to understand the sources of structural health monitoring data, particularly acoustic emission data, in bridges and other structures, such as dams and nuclear plants. Automation of the evaluation of bridges and other structures increases accuracy and minimizes risk to workers and the public. Assessing the structural condition of bridges and other structures as presently disclosed also facilitates automated asset management of transportation systems, such as by state departments of transportation and other bridge/structural owners.