Patent classifications
G01L1/00
Electronic Strut Monitor
A monitor configured to be removably coupled to a strut that forms part of a temporary support structure. The monitor may include an electronic monitoring device that includes a load cell. The monitor may be configured to be position in-line with strut and subject to the same forces exerted upon the strut. Further the monitor may be configured to wirelessly communicate the sensor information to a user.
FRACTURE-VISUALIZATION SENSOR AND FRACTURE-VISUALIZATION SYSTEM USING SAME
To provide a fracture-visualization sensor capable of visualizing the fracture behavior of a composite material and a composite-material fracture-visualization system using the fracture-visualization sensor.
A first luminescent film including a mechanoluminescent material is provided on one surface of a composite material. The first luminescent film has a maximum stress per unit of cross-sectional area within the range of 19-43 N/mm.sup.2.
Method for simulating and analysing an assembly of parts created by a forming process
A computer-implemented method serves for simulating and analysing an assembly of two or more formed sheet metal parts. It comprises simulating a forming process of each part by an approximate simulation (20), and then performing an assembly simulation (40). In order to allow for a quick iteration over different part geometries to assess the assembly, the approximate simulation (20) comprises based on a reference geometry (10) of each part, estimating the deformation of a sheet metal blank required to attain the reference geometry (10); based on this deformation, estimating stresses within the material of the formed part; based on these stresses, estimating the shape of the formed part in which these stresses are in equilibrium, and using this shape as result (31) of the approximate simulation.
DETERMINATION OF RESONANT FREQUENCY AND QUALITY FACTOR FOR A SENSOR SYSTEM
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.
Automated, wireless, cargo restraint tension control and monitoring system
A cargo restraint system a locking ring coupled to an extension tube, wherein the locking ring comprises an annular body and one or more tabs extending from the annular body. The cargo restrain system also includes a locking tube coupled to the main body. The locking tube comprises one or more grooves complementary to the shape and size of the tabs on the locking ring. The grooves of the locking tube inhibit rotational movement of the locking ring.
Force sensing input device utilizing strain gauges
A force sensing device includes a first force sensor and a second force sensor. The first force sensor is configured to output a first force resulting signal and includes a first strain gauge coupled to a first voltage source and a first trace. The first force sensor further includes a second strain gauge coupled to a second voltage source and the first trace. The second force sensor is configured to output a second force resulting signal having a polarity opposite that of the first force resulting signal. The second force sensor includes a first strain gauge coupled to the second voltage source and a second trace, and a second strain gauge coupled to the first voltage source and the second trace.
METHOD FOR IDENTIFYING SPATIAL-TEMPORAL DISTRIBUTION OF VEHICLE LOADS ON BRIDGE BASED ON DENSELY CONNECTED CONVOLUTIONAL NETWORKS
The present invention proposes a method for identifying the spatial-temporal distribution of the vehicle loads on a bridge based on the DenseNet. The method includes five steps: firstly, mounting a plurality of cameras in different positions of a bridge, acquiring images of the bridge from different directions, and outputting video images with time tags; secondly, acquiring multichannel characteristics of vehicles on the bridge by using DenseNet, including color characteristics, shape characteristics and position characteristics; thirdly, analyzing the data and characteristics of the vehicles from different cameras at a same moment to obtain vehicle distribution on the bridge at any time; fourthly, continuously monitoring the vehicle distribution in a time period to obtain a vehicle load situation on any section of the bridge; and finally, integrating the time and space distribution of the vehicles to obtain spatial-temporal distribution of the bridge.
METHOD FOR IDENTIFYING SPATIAL-TEMPORAL DISTRIBUTION OF VEHICLE LOADS ON BRIDGE BASED ON DENSELY CONNECTED CONVOLUTIONAL NETWORKS
The present invention proposes a method for identifying the spatial-temporal distribution of the vehicle loads on a bridge based on the DenseNet. The method includes five steps: firstly, mounting a plurality of cameras in different positions of a bridge, acquiring images of the bridge from different directions, and outputting video images with time tags; secondly, acquiring multichannel characteristics of vehicles on the bridge by using DenseNet, including color characteristics, shape characteristics and position characteristics; thirdly, analyzing the data and characteristics of the vehicles from different cameras at a same moment to obtain vehicle distribution on the bridge at any time; fourthly, continuously monitoring the vehicle distribution in a time period to obtain a vehicle load situation on any section of the bridge; and finally, integrating the time and space distribution of the vehicles to obtain spatial-temporal distribution of the bridge.
Ultrahigh sensitive pressure-sensing film based on spiky hollow carbon spheres and the fabrication method thereof
The present invention relates to an ultrahigh sensitive pressure-sensing film based on spiky hollow carbon spheres and the fabrication method thereof. The fabricated spiky hollow carbon spheres composed polydimethylsiloxane sensing film whose spheres were well dispersed in the matrix. The spiky structure is useful for the spheres to trigger Fowler-Nordheim (F-N) tunneling effect and thus enhancing the sensitivity of the material. The carbon material fabricated by the precursor transformation method contains a proper Nitrogen doping, which has efficiently increased the carrier migration ability. The hollow structure can both regulate the density of fillers and help to improve its temperature independence. Calcine the spheres under an inert atmosphere to transform the spiky hollow organic spheres into a carbon one, in this process the Nitrogen fraction and graphitization can be adjusted. The above carbon spheres then can be assembled with polydimethylsiloxane to achieve the composite film. The material of the present invention exhibits ultrahigh sensitivity, high sensing density, transparent, low hysteresis, temperature noninterference, and its processing method is simple, maturity and environment friendly.
Wearable user input device and sensor system for sports training
A system for monitoring injuries comprising a plurality of wearable user input devices and a wireless transceiver. Each of the plurality of wearable user input devices may be configured to detect motion patterns of a user. Each of the plurality of wearable user input devices may be configured as performance equipment. The wireless transceiver may be configured to communicate the motion patterns to a user device. The user device may be configured to (i) develop and store reference patterns related to impacts, (ii) compare the detected motion patterns with the reference patterns, (iii) estimate a location and direction of an impact based on the comparison, (iv) accumulate data from the estimated impact with previously suffered impact data, (v) aggregate results based on the accumulated impact data and context information and (vi) generate feedback for the user based on the aggregated results.