An AE-signal detecting device for an abrasive wheel includes: an AE sensor which outputs an AE signal upon receipt of an elastic wave generated in an annular abrasive wheel sandwiched between a fixed flange fixed to a rotating shaft and a movable flange provided capable of getting closer to/separating from the fixed flange; a transmission circuit portion which wirelessly transmits the AE signal output from the AE sensor; and a reception circuit portion which receives the AE signal transmitted wirelessly, wherein the AE sensor is disposed on the movable flange or the fixed flange, detects the elastic wave transmitted from the abrasive wheel, and outputs the AE signal.

An unmanned aerial vehicle (UAV) includes a flexible holder retaining a plurality of probes. The flexible holder is deformable to arrange the probes around a portion of a structure, allowing the probes to scan the portion of the structure. At least one of the plurality of probes is an ultrasonic test (UT) probe to scan the portion of the structure with ultrasonic waves.

Aspects of the disclosure include systems, methods, and program products for evaluating the condition of a component using an acoustic sensor embedded within a lighting device. A system according to the present disclosure can include a first lighting device configured to illuminate an area of an industrial plant; a first acoustic sensor embedded within the first lighting device and configured to detect an acoustic signature of a component in the industrial plant; a computing device communicatively connected to the first acoustic sensor and configured to evaluate a condition of the component in the industrial plant based on the acoustic signature.

Methods and devices are provided for analyzing a tubular structure including at least two electromagnetic-acoustic transducers (EMAT) and, called sensors, attachable or attached in, on or in the vicinity of the tubular structure; and computation and/or memory resources, that are accessed locally and/or remotely and that are configured to determine, for the pair of sensors, a function representing the impulse response of the tubular structure on the basis of the diffuse acousto-elastic noise present in the structure. Developments describe the use of rings supporting the sensors; translation and/or rotation movements; permanent or temporary installations; hinged rings; various computation modes, e.g., intercorrelation, a passive inverse filter, or correlation of the coda of the correlation; the use of artificial noise sources, imaging (e.g., tomography) for determining the existence of one or more defects in the structure. Software aspects are described.

An ultrasonic patch transducer is configured to be secured to an outer surface of a structural asset, such as a pipe or pressure vessel, for condition monitoring. The ultrasonic patch transducer includes a housing defining a centerline between a first end of the housing and a second end of the housing, a piezoelectric element within the housing and positioned along the centerline, and at least two magnets within the housing and positioned along the centerline. The at least two magnets and the piezoelectric element are configured to be positioned along a tangent plane of the structural asset.

Systems and methods are disclosed for detecting a crack in an automotive windshield and alerting a user of the same. This can allow the user to repair the crack before the user might otherwise detect the crack by his/her own visual inspection. The windshield can be provided with emitters configured to emit signals (e.g., sound, light, etc.) and corresponding detectors configured to detect the emitted signals. Signal profiles or signatures can be stored that represent normal measurements when there is no crack. Upon detecting a signal signature that deviates from the stored normal signal signatures, the system can notify the user of a potential crack in the windshield. The system can also determine the location of the crack based upon which of the detectors detect a change in the detected signal.

The present invention discloses a boom monitoring method and engineering machinery comprising a boom monitoring system. The method comprises obtaining a boom damage signal monitored in boom operation by a piezoelectric sensing network formed by a plurality of piezoelectric sensors arranged at different points on a boom, and determining a damage position of the boom and a corresponding first boom damage value such that when the first boom damage value reaches a preset starting value of an optical fiber sensing network formed by a plurality of optical fiber sensors arranged at the different monitoring points on the boom, optical wave values of the corresponding monitoring points are obtained and a boom crack signal is determined. A second boom damage value is calculated according to the boom crack signal, which comprises a crack change factor and a crack length. According to the present invention, the boom is monitored with improved efficiency.

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.

According to one embodiment, a sensor module includes a sensor and a diagnosis circuit. The sensor includes piezoelectric transducers and switches. The piezoelectric transducers have different resonance frequencies. The switches are provided to correspond to the piezoelectric transducers, respectively. Each of the switches outputs an output signal corresponding to a voltage generated by an inverse piezoelectric effect of a corresponding piezoelectric transducer of the piezoelectric transducers. The diagnosis circuit diagnoses, based on a difference in pattern of the output signal, whether vibration has newly occurred in the sensor, and switch an output destination of the output signal of the sensor according to a result of the diagnosis.

A MEMS AE transducer system is provided that takes advantage of the low power consumption and lightweight characteristics of MEMS AE transducers, while also achieving higher sensing sensitivity. To address the problem of low sensitivity typically associated with MEMS AE transducers, electrical responses of multiple MEMS AE transducers operating at different frequency ranges are combined to increase the bandwidth and sensitivity of the MEMS AE transducer system. As the frequencies are constructive, the combined response on a single channel is the actual summation of two signals with an improved signal to noise ratio. Additionally, each frequency can be decomposed because they are well separated from each other due to the super narrowband response and high Quality factor of MEMS AE transducers.