Provided is a sensor and method for weld defect detection. The sensor includes several piezoelectric elements which form a matrix arranged on a flexible substrate. Each piezoelectric element is covered with a damping block and surrounded by sound absorbing material, and packaged within a flexible protective film. The sensor is simple, highly adaptable and high detection efficiency, which is especially suitable for the quick in-service inspection of long distance welds in large equipment, it has high degree of automation.

A system includes one or more tools, sensors, or both configured to obtain data related to the one or more pipelines, wherein the data is ultrasonic data, electromagnetic data, or both, and a cloud-based computing system including at least one processor that receives the data from the one or more tools, sensors, or both, performs analysis to generate a virtual structural model of the one or more pipelines based on the data, determines one or more states of the one or more pipelines using the virtual structural model and determines whether to take one or more actions when the one or more states indicate that the one or more pipelines violate a threshold operation boundary.

An ultrasonic testing device includes: a signal acquiring unit which receives a reflected echo signal relating to a reflected echo of ultrasonic waves from an object being inspected, a defect detecting unit which detects a defect of the object being inspected on the basis of the reflected echo signal, and a display unit which displays the detection result of the defect detecting unit. The defect detecting unit uses the maximum signal strength of the reflected echo signal exceeding a first threshold value to detect the defect. The first threshold value is a value with which the signal strength is less than the maximum signal strength of the reflected echo signal from the surface of the object, using as an evaluation range an interval between a position which is positioned a first distance from the surface of the object and a bottom surface of the object.

A system includes one or more tools, sensors, or both configured to obtain data related to the one or more pipelines, wherein the data is ultrasonic data, electromagnetic data, or both, and a cloud-based computing system including at least one processor that receives the data from the one or more tools, sensors, or both, performs analysis to generate a virtual structural model of the one or more pipelines based on the data, determines one or more states of the one or more pipelines using the virtual structural model and determines whether to take one or more actions when the one or more states indicate that the one or more pipelines violate a threshold operation boundary.

This method comprises: a step of reconstructing the acoustic signal produced during the occurrence or the evolution of the defect, this reconstruction step comprising constructing an estimate S.sub.e(w) of the signal produced at the position of the defect based on an ultrasonic signal F.sub.j(t) measured by a sensor and using an estimate or a measurement of a product R.sub.j(w)G.sub.j(w) that relates, in the frequency domain, the measured ultrasonic signal F.sub.j(w) to the produced acoustic signal S(w), and a step of automatically classifying the acoustic source, carried out based on the estimate of the reconstructed acoustic signal.

A method for detecting faults in plates includes the steps of: transmitting an acoustic signal towards the plate from a transmitting transducer, and receiving the acoustical signal from the plate in a receiving transducer. The receiving transducer is mounted at a distance from the transmitting transducer. The method includes the further steps of identifying zones of the plate wherein energy levels of the received signals are attenuated compared to other zones of the plate, and comparing the energy levels of the A.sub.2 and S.sub.3 guided Lamb modes in the received signals in the identified zones.

Disclosed herein are a method and apparatus for sensing an impact on a vehicle based on an acoustic sensor and an acceleration sensor. The method of sensing an impact on a vehicle may include obtaining information related to an impact sound generated in the vehicle of a user and around the vehicle of the user through an acoustic sensor, obtaining information related to an impact applied to the vehicle of the user through an impact detection sensor, and determining an impact sound directly generated in the vehicle of the user based on the information related to the impact sound and the information related to the impact.

Methods, devices, and systems for detecting one or more discontinuities of a structure may include a laser emitter configured to generate and direct an ultrasonic signal into a structure and a receiver comprising an optical microphone. The optical microphone may comprise an array of optical microphones configured in a complementary manner to the emitter.

An ultrasonic inspection system performs a method of inspecting a layer of a component formed on a build plate using an additive manufacturing process. The inspecting includes delivering to the layer, through the build plate and any intervening layers of the component previously formed on the build plate, an ultrasonic chirp pulse having a frequency that sweeps through a range of frequencies across a chirp bandwidth. The method also includes receiving from the layer ultrasonic energy including reflections of the ultrasonic chirp pulse delivered to the layer, and processing the ultrasonic energy to produce an ultrasonic signature indicative of a characteristic of the layer and the intervening layers. The inspecting is repeated for each of subsequent layers of the component formed on the build plate according to the additive manufacturing process to inspect the component layer-by-layer as the component is built-up during the additive manufacturing process.

A feedback and feedforward as well as a statistical predictive control system and method for continuously controlling texture of a food snack in a manufacturing process. The feedback system includes a quantitative texture measuring tool that is positioned downstream of a food processing unit. The texture measuring tool continuously measures a texture attribute of food snack from the food processing unit and feeds back texture attribute information to a controller that controls input parameters to food processing unit such that the texture attribute of a resultant food snack falls within an acceptable limit. The texture measuring tool comprises an excitation tool that strikes the food snack and produces an acoustic signal that is processed by a data processing unit. The data processing unit identifies relevant frequencies in the acoustic signal and quantitatively measures a texture attribute based on a correlated model that includes the relevant frequencies.