Detecting and classifying damage to a vehicle. One example system includes a microphone positioned to detect sound waves inside the vehicle, one or more sensors positioned on the vehicle and configured to sense a characteristic of a windshield of the vehicle, and an electronic processor communicatively coupled to the one or more sensors and the microphone. The electronic processor is configured to receive sensor information from the one or more sensors and to receive an electrical signal from the microphone. The electronic processor is configured to determine, based on the sensor information, whether a crack event has occurred. The electronic processor is configured to, in response to determining that a crack event has occurred, determine a cause of the crack event based on the electrical signal received from the microphone. The electronic processor is configured to execute a mitigation action based on the cause of the crack event.

According to one embodiment, a structure evaluation system of the embodiments includes a plurality of sensors, an arrival time determiner, a reliability calculator, and a map generator. The plurality of sensors detect elastic waves. The arrival time determiner determines arrival times of the elastic waves using elastic waves detected by the plurality of respective sensors. The reliability calculator calculates reliabilities related to measurement waveforms of the elastic waves on the basis of the arrival times. The map generator generates a first map on the basis of the calculated reliabilities or the reliabilities and a distance.

Disclosed is a method for determining a whole macro-micro process of rock deformation and failure based on a four-parameter test, including following steps: firstly, obtaining acoustic emission data and deformation data of a sample in a compression test, and then calculating the deformation data according to a finite deformation theory to obtain a mean rotation angle θ at each stress level; using Grassberger-Procaccia (G-P) algorithm to calculate the acoustic emission data, and obtaining a fractal dimension of a temporal distribution D.sub.T of an acoustic emission signal and calculating a fractal dimension of a spatial distribution D.sub.S; obtaining a microscopic morphology of a fracture surface by scanning electron microscope (SEM) test after the compression test, and calculating a fractal dimension D.sub.A of the fracture surface; finally, obtaining a mathematical trend relationship between θ and D.sub.T, D.sub.S and D.sub.A according to a comprehensive analysis of D.sub.T, D.sub.S, D.sub.A and θ.

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.

A non-destructive process of inspecting an object can include positioning a first and second ultrasonic element relative to the body of the object and offsetting the first and second ultrasonic elements in a direction orthogonal to a longitudinal axis of the body. A further process of inspecting an object can include creating a map of the body of the object including at least one anomaly and providing a quality value associated with the body based on evaluation of one or more criteria selected from the group consisting of the type, number, size, shape, position, orientation, edge sharpness, and any combination thereof of the at least one anomaly. An ultrasonic system can include a first and second ultrasonic element and a processing element. The process element can be configured to create a map of the body including at least one anomaly and provide a quality value associated with the body based on evaluation of one or more criteria selected from the group consisting of the type, number, size, shape, position, orientation, edge sharpness, and any combination thereof of the at least one anomaly.

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes acquiring first sound data collected by a first microphone and second sound data collected by a second microphone during traveling of a vehicle in which the first microphone is provided in vicinity of a front wheel and the second microphone is provided in vicinity of a rear wheel; and detecting a cavity under a road surface where the vehicle has traveled based on a difference between the acquired first sound data and the acquired second sound data.

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.

An asphalt density estimation system includes a measurement device configured to output a measurement signal; a time synchronization unit configured to sample the measurement signal to obtain a sampled measurement signal and identify periodic sampling points of the sampled measurement signal across a plurality of periods. The system also includes a time synchronous averaging unit configured to construct a modified measurement signal in the time domain by: for at least one sampling point within the period, averaging a plurality of the periodic sampling points across periods to obtain an average periodic data point for the at least one sampling point, and constructing the modified measurement signal using the average periodic data point for the at least one sampling point. The system further includes a density calculation unit configured to determine asphalt density values based on the modified measurement signal; and a display unit configured to display the determined asphalt density values.

Provided is a hammering test system. A hammering test system includes a hammering test device including a target, a traveling mechanism for automatically traveling on a to-be-tested surface, a marking mechanism configured to perform marking on the to-be-tested surface, an adsorbing mechanism for adsorbing to the to-be-tested surface, and a hammering test mechanism configured to conduct a hammering test on the to-be-tested surface, and a surveying instrument capable of performing automatic tracking and distance and angle measurements of the target. A hammering test is conducted by causing the hammering test device to travel to a desired position while adsorbing to a to-be-tested surface by the adsorbing mechanism. When it is determined that there is an abnormality, a marking is marked on the to-be-tested surface. The surveying instrument automatically tracks the target, and when conducting a hammering test, makes distance and angle measurements of the target.

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.