A sensor includes a body member, a volume change body, and a detection member. The body member has a flat plate-like shape, a first end in a first direction being supported, and a storage space opening at at least one of both end faces in a thickness direction. The volume change body, whose volume changes depending on an amount of a target, is supported by the body member so that at least a part of the volume change body is stored in the storage space. The detection member is in contact with a second end in the first direction of the body member, and detects stress caused by the change in the volume of the volume change body.

A resonant sensor comprises a proof body subjected to a torque of forces produced by an external mechanical structure, the body comprising: a first and a second interface that can each come into contact with the structure; at least two sensitive zones arranged between these two interfaces; a sensitive zone formed by a plate embedded in a frame secured mechanically to the interfaces, the plate able to resonate under the effect of local mechanical excitations produced at particular points by excitation transducers bearing the plate at several resonant frequencies, sensors picking up the resonant signals produced at the particular points, measurement means measuring the resonant frequency shifts of signals which are linear combinations of the resonant signals picked up, the shifts being a function of mechanical stresses induced by the forces and transmitted to the plate by the frame, the components of the torque of forces being determined from the resonant frequency shifts measured on the plates of the sensitive zones.

The present invention relates to a structural health monitoring system, for example a system used in the non-destructive evaluation of an aircraft structure. The present invention provides a method and apparatus for evaluating one or more anomalies within a structure using a structural health monitoring system that includes at least three transducers arranged in operative contact with the structure such that no two transducers are aligned to be parallel. A transducer excites an elastic wave that propagates through the structure, and reflections from any anomalies within the structure are collected by the three transducers. These collected signals are analyzed to identify an anomaly within the structure. Time of flight techniques are used to determine the location of the anomaly.

A sensor includes a body member, a volume change body, and a detection member. The body member has a flat plate-like shape, a first end in a first direction being supported, and a storage space opening at at least one of both end faces in a thickness direction. The volume change body, whose volume changes depending on an amount of a target, is supported by the body member so that at least a part of the volume change body is stored in the storage space. The detection member is in contact with a second end in the first direction of the body member, and detects stress caused by the change in the volume of the volume change body.

A method for determining sensor parameters of an actively-driven sensor system may include obtaining as few as three samples of a measured physical quantity versus frequency for the actively-driven sensor system, performing a refinement operation to provide a refined version of the sensor parameters based on the as few as three samples and based on a linear model of an asymmetry between slopes of the measured physical quantity versus frequency between pairs of the as few as three samples, iteratively repeating the refinement operation until the difference between successive refined versions of the sensor parameters is below a defined threshold, and outputting the refined sensor parameters as updated sensor parameters for the actively-driven sensor system.

Disclosed are a preparation method for a graphene aerogel array sensor and use thereof. A miniature graphene aerogel array device is prepared by combining in-situ printing and solvent plasticization and foaming, which has excellent flexibility and stability, and is suitable for use in a variety of scenarios, such as sensors, and energy storage devices, etc. The array sensor provided in the present disclosure exhibites extremely high stability, high accuracy and reliability. Combining with deep machine learning, the array sensor can be endowed with the function of learning and recognition of machine intelligence, thus greatly promoting the development of the next generation of artificial intelligence.

A transducer structure for converting a deformation along an axis into a corresponding deformation on a plane orthogonal to the axis itself, including: two end plates facing each other and aligned along a common reference axis (X); connection members projecting radially from each end plate according to respective different directions; lateral bars connecting the end plates to one another through two connection members. The connection members are deformable within respective deformation planes to allow relative movements between the end plates and the lateral bars such as to convert an axial movement of mutual approach between the two end plates into a corresponding radial movement of the lateral bars away from the reference axis (X), and vice-versa.

A bearing detection device comprises: a housing body (2) having a substantially annular shape, prearranged for being fixed to a stationary ring (6a) of a bearing (6); and a detection arrangement on the housing body (2), comprising at least one piezoelectric transducer (10; 20). The detection arrangement further comprises: a floating body (7) having a substantially annular shape, which is mounted within the housing body (2) and is able to amplify mechanically vibrations of the bearing (6); a sensor unit (8) having a substantially annular shape, which is set in a substantially stationary position on the housing body (2), the supporting body (81) having a detection surface (8a) that is configured for receiving thereon, directly or via interposition of at least one further element, a corresponding surface of the floating body (7). The at least one piezoelectric transducer (10; 20) defines at least part of the detection surface (8a) and is configured for generating an electrical potential difference that is substantially proportional to the magnitude of a stress or force exerted by the floating body on the at least one piezoelectric transducer (10; 20).

A pressure detecting circuit may include a pressure sensing circuit (101), a signal generating circuit (102), and a frequency detecting circuit (103). The pressure sensing circuit (101) and the signal generating circuit (102) may be configured to constitute an oscillating circuit (104). The signal generating circuit (102) may be configured to generate an oscillating signal based on a pressure sensed by the pressure sensing circuit (101). The frequency detecting circuit (103) may be configured to detect a frequency of the oscillating signal and determine a value of the pressure sensed by the pressure sensing circuit (101) based on the frequency of the oscillating signal.

System and methods are provided for characterizing an internal surface of a lens using interferometry measurements. Sphere-fitting a distorted radius determines distorted pathlengths. Ray-tracing simulates refraction at all upstream surfaces to determine a cumulative path length. A residual pathlength is scaled by the group-index and rays are propagated based on the phase-index. After aspheric surface fitting, a corrected radius is determined. To estimate a glass type for the lens, a thickness between focal planes of the lens surfaces is determined using RCM measurements. Then, for both surfaces, the surface is positioned into focus, interferometer path length matching is performed, a reference arm is translated to stationary phase point positions for three wavelengths to determine three per-color optical thicknesses, and ray-tracing is performed. A glass type is identified by minimizing an error function based on optical parameters of the lens and parameters determined from known glass types from a database.