A Novel Method of Planar Near-Field Scattering Measurements

2015 ◽

Author(s):

Jeff Dunnihoo ◽

Pasi Tamminen ◽

Toni Viheriäkoski

Keyword(s):

Near Field ◽

Electronic Systems ◽

Inexpensive Method ◽

Scanning Method ◽

Field Information ◽

Novel Method ◽

Near Field Scanning

Abstract In this study we present a novel method to use a field collapse method together with fully automated near field scanning equipment to construct E- and H-field information of a system during transient ESD events. This inexpensive method provides an alternative way for system designers to validate and analyze the EMC/ESD capability of electronic systems without TLP pulsers, ESD simulators, or precision inductive current probes.

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Novel Method for Selection of Regularization Parameter in the Near-field Acoustic Holography

Chinese Journal of Mechanical Engineering ◽

10.3901/cjme.2011.02.285 ◽

2011 ◽

Vol 24 (02) ◽

pp. 285 ◽

Cited By ~ 5

Author(s):

Yongbin ZHANG

Keyword(s):

Regularization Parameter ◽

Near Field ◽

Acoustic Holography ◽

Novel Method ◽

Selection Of

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Real-Time Monitoring of Jet Trajectory during Jetting Based on Near-Field Computer Vision

Sensors ◽

10.3390/s19030690 ◽

2019 ◽

Vol 19 (3) ◽

pp. 690 ◽

Cited By ~ 2

Author(s):

Jinsong Zhu ◽

Wei Li ◽

Da Lin ◽

Ge Zhao

Keyword(s):

Computer Vision ◽

Prediction Model ◽

Real Time ◽

Processing Time ◽

Near Field ◽

Image Correction ◽

Noise Elimination ◽

Sensor Device ◽

Jet Trajectory ◽

Novel Method

A novel method of near-field computer vision (NFCV) was developed to monitor the jet trajectory during the jetting process, which was used to precisely predict the falling point position of the jet trajectory. By means of a high-resolution webcam, the NFCV sensor device collected near-field images of the jet trajectory. Preprocessing of collected images was carried out, which included squint image correction, noise elimination, and jet trajectory extraction. The features of the jet trajectory in the processed image were extracted, including: start-point slope (SPS), end-point slope (EPS), and overall trajectory slope (OTS) based on the proposed mean position method. A multiple regression jet trajectory range prediction model was established based on these trajectory characteristics and the reliability of the model was verified. The results show that the accuracy of the prediction model is not less than 94% and the processing time is less than 0.88s, which satisfy the requirements of real-time online jet trajectory monitoring.

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Biomimetic tough helicoidally structured material through novel electrospinning based additive manufacturing

MRS Advances ◽

10.1557/adv.2019.313 ◽

2019 ◽

Vol 4 (43) ◽

pp. 2345-2354 ◽

Cited By ~ 2

Author(s):

Komal Agarwal ◽

Rahul Sahay ◽

Avinash Baji ◽

Arief S. Budiman

Keyword(s):

Structural Design ◽

Polyvinylidene Fluoride ◽

Architectural Design ◽

Mechanical Characteristics ◽

Near Field ◽

Structural Materials ◽

Electrospinning Technique ◽

Mantis Shrimp ◽

Novel Method ◽

Microstructural Design

ABSTRACTNatural structural materials (NSMs) such as nacre, teeth, bones and crustacean exoskeleton are usually made of weak biomaterials arranged in specific structural design imparting them remarkable mechanical characteristics. Such hierarchical structural layouts found in nature encourage designing of mechanically desirable synthetic structural materials (SSMs). Among variety of natural hierarchical layouts, this paper specifically focuses on helicoidal architectural design found in the tough dactyl club of mantis shrimp. We first decode the mechanics behind helicoidal microstructural design and document the development of impact resistant macroscale helicoidal architectured synthetic structural materials (HA-SSMs). Next, near-field electrospinning technique (NFES)- both melt (polycaprolactone) and solution (polyvinylidene fluoride) type has been discussed in detail, as a novel method for developing lab scale 3D biomimetic HA-SSMs in micro-nanoscale. Further, the effect of the helical arrangement, size of substructures and surface treatment on strength and toughness of NFES fabricated HA-SSMs samples is analysed.

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Determination of particle size distribution based on dynamic light scattering measurements in the near field

Optics and Lasers in Engineering ◽

10.1016/j.optlaseng.2019.105980 ◽

2020 ◽

Vol 127 ◽

pp. 105980

Author(s):

Biao Zhang ◽

Chen Wang ◽

Zhao-Long Song ◽

Chuan-Long Xu ◽

Zhen-Zong He

Keyword(s):

Particle Size ◽

Light Scattering ◽

Dynamic Light Scattering ◽

Particle Size Distribution ◽

Size Distribution ◽

Near Field ◽

Scattering Measurements

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Support Vector Regression for the Modeling and Synthesis of Near-Field Focused Antenna Arrays

Electronics ◽

10.3390/electronics8111352 ◽

2019 ◽

Vol 8 (11) ◽

pp. 1352 ◽

Cited By ~ 1

Author(s):

Rafael González Ayestarán

Keyword(s):

Support Vector Regression ◽

Antenna Arrays ◽

Near Field ◽

Computational Cost ◽

Support Vector ◽

Analysis Tool ◽

Training Samples ◽

Learning Capabilities ◽

Novel Method ◽

The Individual

The powerful support vector regression framework is proposed in a novel method for near-field focusing using antenna arrays. By using this machine-learning method, the set of weights required in the elements of an array can be calculated to achieve an assigned near-field distribution focused on one or more positions. The computational cost is concentrated in an initial training process so that the trained system is fast enough for applications where moving devices are involved. The increased learning capabilities of support vector machines allow using a reduced number of training samples. Thus, these training samples may be generated with a prototype or a convenient electromagnetic analysis tool, and hence realistic effects, such as coupling or the individual radiation patterns of the elements of the arrays, are accounted for. Illustrative examples are presented.

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