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公开(公告)号:US20240361280A1
公开(公告)日:2024-10-31
申请号:US18764878
申请日:2024-07-05
发明人: David A. Jack , John E. Fitch , Theresa Vo
CPC分类号: G01N29/4472 , G01N29/07 , G01N29/11 , G01N29/46 , G01N2291/0231 , G01N2291/2638
摘要: Embodiments are disclosed for characterizing and quantifying composite laminate structures. The embodiments take a composite laminate of unknown ply stack composition and sequence and determine various information about the individual plies, such as ply stack, orientation, microstructure, and type. The embodiments distinguish between weave types that exhibit similar planar stiffness behaviors, but produce different failure mechanisms. Individual ply information is then used to derive the laminate bulk properties from externally provided constitutive properties of the fiber and matrix, including extensional stiffness, bending-extension coupling stiffness, bending stiffness, and the like. The laminate bulk properties are then used to generate a probabilistic failure envelope for the composite laminate. In some embodiments, ply stack type and sequence are also determined for a curved composite laminate using the disclosed embodiments by adding a rotational stage.
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公开(公告)号:US20240280545A1
公开(公告)日:2024-08-22
申请号:US18444567
申请日:2024-02-16
申请人: BAYLOR UNIVERSITY
发明人: Luke W. Battershell , David A. Jack , Trevor Fleck
CPC分类号: G01N29/46 , G01B17/02 , G01N15/088 , G01N29/043 , G01N2291/0231
摘要: A method for ultrasonic inspection of fused filament fabrication (FFF) manufactured samples and of carbon fiber reinforced polymer (CFRP) laminates is disclosed that includes performing a time-frequency transforms including the short-time Fourier transform (STFT) and the wavelet synchrosqueezed transform (WSST), inspecting features in FFF manufactured samples for porosity, layer height and missing extrudate and visualizing CFRP laminate wrinkle.
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3.
公开(公告)号:US20240239018A1
公开(公告)日:2024-07-18
申请号:US18557093
申请日:2022-04-25
发明人: Masatoshi OHARA , Kentaro TAKI
CPC分类号: B29B7/72 , B29B7/48 , G01N29/14 , G01N29/4427 , G01N29/4472 , G01N29/46 , G01N2291/0231
摘要: A kneading state detection device includes an acquisition unit that, when an extrusion molding machine that kneads a raw material or kneads a raw material and an additive is in operation, acquires an output of an AE sensor installed on a housing of the extrusion molding machine, and a determination unit that determines a kneading state of the raw material, based on a comparison between a change in intensity of the output of the AE sensor acquired by the acquisition unit and a threshold.
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公开(公告)号:US11931818B2
公开(公告)日:2024-03-19
申请号:US17497390
申请日:2021-10-08
发明人: Felix Klimas , Thomas Herzing , Lutz Lehmann , Daniel Zemann
CPC分类号: B23K20/10 , B23K20/106 , B23K31/125 , G01N29/12 , G01N29/4481 , G01N29/46 , G01N2291/012 , G01N2291/018 , G01N2291/267
摘要: A method for non-destructive testing of a quality of an ultrasonic weld from a welding process includes detecting of a time-dependent measurement value over a period of time, where the measurement value is characteristic of a mechanical or electrical vibration behavior of a welding process to be tested. The method includes evaluating a measurement-value course of the detected time-dependent measurement value by using a Fourier analysis. The method further includes comparing a result of the evaluation to a reference value in order to test the quality of the weld. A measuring device and an ultrasonic welding system are also included.
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公开(公告)号:US11927563B2
公开(公告)日:2024-03-12
申请号:US17288560
申请日:2020-10-28
申请人: NANTONG UNIVERSITY
发明人: Liang Hua , Ling Jiang , Juping Gu , Cheng Lu , Kun Zhang , Kecai Cao , Liangliang Shang , Qi Zhang , Shenfeng Wang , Yuxuan Ge , Zixi Ling , Jiawei Miao
IPC分类号: G01N33/207 , B23K37/00 , G01N29/04 , G01N29/46 , G06N3/08 , G06T7/11 , H04R1/08 , H04R3/04 , B23K31/00 , B23K31/12 , G01N29/34 , G01N29/44
CPC分类号: G01N29/045 , B23K37/00 , G01N29/46 , G01N33/207 , G06N3/08 , H04R3/04 , B23K31/006 , B23K31/125 , G01N29/348 , G01N29/4481 , G01N2291/0234 , G01N2291/0289 , G01N2291/267 , G01N2291/2675 , G06T7/11 , G06T2207/20084 , H04R1/08
摘要: A smart acoustic information recognition-based welded weld impact quality determination method and system, comprising: controlling a tip of an ultrasonic impact gun (1) to perform impact treatment on a welded weld with different treatment pressures, treatment speeds, treatment angles and impact frequencies, obtaining acoustic signals during the impact treatment, calculating feature values of the acoustic signals, and constructing an acoustic signal sample set including various stress conditions; marking the acoustic signal sample set according to impact treatment quality assessment results for the welded weld; establishing a multi-weight neural network model, and using the marked acoustic signal sample set to train the multi-weight neural network model; obtaining feature values of welded weld impact treatment acoustic signals to be determined, inputting the feature values into the trained multi-weight neural network model, and outputting determination results for welded weld impact treatment quality to be determined.
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公开(公告)号:US20240077454A1
公开(公告)日:2024-03-07
申请号:US18457885
申请日:2023-08-29
发明人: Jiaye WU , Biao SU , Hongyin WANG , Xiujuan LIU , Jing CHEN , Wei WANG , Hui XIE
CPC分类号: G01N29/045 , G01N29/46 , G01N2291/023
摘要: Provided are an elastic wave radar detection device and method. The device includes a vibration excitation device, a first sensor, a second sensor, and a controller. The first sensor is arranged on the vibration excitation device, and the second sensor is arranged on a detected object. The first sensor is used to collect vibration excitation information, namely, an incident signal, and the second sensor is used to collect information of the detected object, namely, a vibration signal. Both the first sensor and the second sensor are connected to the controller. The elastic wave radar detection device and method provided by the present disclosure can receive vibration excitation information and introduce a standard incident signal, so as to achieve the uniformity of signals and improve the detection accuracy.
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公开(公告)号:US11892344B2
公开(公告)日:2024-02-06
申请号:US17721882
申请日:2022-04-15
申请人: Cornell University
发明人: Amit Lal
CPC分类号: G01H11/08 , G01N29/46 , G06F17/142 , H10N30/50 , H10N30/85 , G01N2291/0426 , H04B11/00
摘要: A device configured for low-energy ultrasonic 2D Fourier transform analysis, comprising: (i) a first layer comprising an array of piezoelectric pixels; (ii) a second layer comprising an array of piezoelectric pixels; (iii) a third layer, positioned between the first and second layers, comprising a bulk ultrasonic transmission medium; wherein the second layer of array of piezoelectric pixels is in the Fourier plane of an input signal of the first layer array of piezoelectric pixels.
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公开(公告)号:US20240036004A1
公开(公告)日:2024-02-01
申请号:US18024934
申请日:2021-09-14
申请人: SUPERSONIC IMAGINE , CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - CNRS , ECOLE SUPÉRIEURE DE PHYSIQUE ET DE CHIMIE INDUSTRIELLES DE LA VILLE DE PARIS
IPC分类号: G01N29/032 , G01N29/46
CPC分类号: G01N29/032 , G01N29/46 , G01N2291/015
摘要: Method for ultrasonic characterization of a medium, comprising a step of generating a series of incident ultrasonic waves, a step of generating an experimental reflection matrix Rui(t) defined between the emission basis (i) as input and a reception basis (u) as output, a step of determining a focused reflection matrix RFoc(rin, rout, δt) of the medium between an input virtual transducer (TVin) calculated based on a focusing as input to the experimental reflection matrix and an output virtual transducer (TVout) calculated based on a focusing as output from the experimental reflection matrix, the responses of the output virtual transducer (TVout) being obtained at a time instant that is shifted by an additional delay δt relative to a time instant of the responses of the input virtual transducer (TVin).
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公开(公告)号:US11885661B2
公开(公告)日:2024-01-30
申请号:US17171795
申请日:2021-02-09
申请人: Wiliot, Ltd.
发明人: Ido Zelman , Matan Epstein , Shay Moshe , Tsvika Rabkin , David Lipshitz , Tal Szpruch , Dotan Ziv , Alon Yehezkely
IPC分类号: G01F23/28 , G01F23/284 , G06N20/00 , G16H20/17 , G01F23/296 , G01N29/34 , G01N29/44 , G01N29/46 , G06F18/21
CPC分类号: G01F23/284 , G01F23/296 , G01N29/348 , G01N29/4454 , G01N29/46 , G06F18/217 , G06N20/00 , G16H20/17 , G06F2218/08 , G06F2218/12
摘要: A system and method for detecting material type using low-energy sensing are disclosed. The method includes receiving frequency words from a tag attached to a container containing material, wherein the tag provides a low-energy sensing configured to transmit the frequency words; extracting at least a first data feature from the received frequency words, wherein the first data feature changes in response to a type of material in the container; classifying the extracted data feature to label a type of the material in the container; and sending a notification indicating the type of material in the container.
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10.
公开(公告)号:US20240003855A1
公开(公告)日:2024-01-04
申请号:US18176432
申请日:2023-02-28
发明人: Zhenghua QIAN , Zhi QIAN , Peng LI , Chen YANG
CPC分类号: G01N29/46 , G01N29/041 , G01N2291/2636 , G01N2291/0427 , G01N2291/023
摘要: The present disclosure belongs to the technical field of ultrasonic non-destructive testing, and discloses a method for extracting feature path signals of pipeline ultrasonic helical guided waves. The method includes: transforming a nonlinear wave number relationship of a pipe wall into a linear form by first order Taylor expansion, the approximation being reasonable under narrow band excitation; on this basis, establishing multimodal and multipath guided wave propagation over-complete data sets, and obtaining a modal weight factor and a path weight factor through a single-layer neural network algorithm; and multiplying the modal weight factor by the multimodal data set to separate a plurality of groups of unimodal signals from a whole signal, and multiplying the path weight factor by the multipath data set to extract unimodal feature path signals. The present disclosure can effectively extract unimodal unipath guided wave feature signals and improve the signal identification, and has broad prospects.
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