A Detection System with Spider Web Coil-Based Wireless Charging and an Active Battery Management System

The article presents a detection system with spider web coil-based wireless charging. Commonly available metal detectors are sold as handheld systems, which enable only progressive, lengthy, time-consuming search. Importantly, a part of the investigated area can thus be easily missed, and the probability that a metal object will not be found increases substantially. This problem, however, is eliminable via the automatic position tracking mode embedded in the solution obtained through our research. The proposed system facilitates using the spider web coil simultaneously for wireless charging and metal detection by pulse induction. The topology of the detector can emit variable pulse lengths, thus allowing the device to detect more types of metal and to adapt itself to the permeability of the soil. The coil has a branch in a relevant part of the winding to reduce undesirable electromagnetic interference during the charging. On the transmitting side of the topology, impedance matching is included to maintain the maximum spatial gap variability. By changing the position of the receiving side, the output voltage changes; therefore, a high efficiency DC/DC converter is employed. The individual battery cells demonstrate different internal resistances, requiring us to apply a new method to balance the cells voltage. The system can be utilized on self-guided vehicles or drones; advantageously, a GPS resending the coordinates to a mesh radio allows for accurate positioning. With the mesh topology, potential cooperation between the multiple systems is possible. The setup utilizes the same coil for wireless power transfer and detection.

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Layered Foam/Film Polymer Nanocomposites with Highly Efficient EMI Shielding Properties and Ultralow Reflection

Nano-Micro Letters ◽

10.1007/s40820-021-00759-4 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Li Ma ◽

Mahdi Hamidinejad ◽

Biao Zhao ◽

Caiyun Liang ◽

Chul B. Park

Keyword(s):

Electromagnetic Interference ◽

High Efficiency ◽

Wave Attenuation ◽

Impedance Matching ◽

Film Structure ◽

Shielding Effectiveness ◽

Emi Shielding ◽

Multiple Reflections ◽

Emi Shielding Effectiveness ◽

Foam Film

AbstractLightweight, high-efficiency and low reflection electromagnetic interference (EMI) shielding polymer composites are greatly desired for addressing the challenge of ever-increasing electromagnetic pollution. Lightweight layered foam/film PVDF nanocomposites with efficient EMI shielding effectiveness and ultralow reflection power were fabricated by physical foaming. The unique layered foam/film structure was composed of PVDF/SiCnw/MXene (Ti3C2Tx) composite foam as absorption layer and highly conductive PVDF/MWCNT/GnPs composite film as a reflection layer. The foam layer with numerous heterogeneous interfaces developed between the SiC nanowires (SiCnw) and 2D MXene nanosheets imparted superior EM wave attenuation capability. Furthermore, the microcellular structure effectively tuned the impedance matching and prolonged the wave propagating path by internal scattering and multiple reflections. Meanwhile, the highly conductive PVDF/MWCNT/GnPs composite (~ 220 S m−1) exhibited superior reflectivity (R) of 0.95. The tailored structure in the layered foam/film PVDF nanocomposite exhibited an EMI SE of 32.6 dB and a low reflection bandwidth of 4 GHz (R < 0.1) over the Ku-band (12.4 − 18.0 GHz) at a thickness of 1.95 mm. A peak SER of 3.1 × 10–4 dB was obtained which corresponds to only 0.0022% reflection efficiency. In consequence, this study introduces a feasible approach to develop lightweight, high-efficiency EMI shielding materials with ultralow reflection for emerging applications.

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Adaptive Detection of Direct-Sequence Spread-Spectrum Signals Based on Knowledge-Enhanced Compressive Measurements and Artificial Neural Networks

Sensors ◽

10.3390/s21072538 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2538

Author(s):

Shuang Zhang ◽

Feng Liu ◽

Yuang Huang ◽

Xuedong Meng

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Spread Spectrum ◽

High Efficiency ◽

Detection System ◽

Direct Sequence Spread Spectrum ◽

Detection Performance ◽

Detection Methods ◽

Direct Sequence ◽

Artificial Neural

The direct-sequence spread-spectrum (DSSS) technique has been widely used in wireless secure communications. In this technique, the baseband signal is spread over a wider bandwidth using pseudo-random sequences to avoid interference or interception. In this paper, the authors propose methods to adaptively detect the DSSS signals based on knowledge-enhanced compressive measurements and artificial neural networks. Compared with the conventional non-compressive detection system, the compressive detection framework can achieve a reasonable balance between detection performance and sampling hardware cost. In contrast to the existing compressive sampling techniques, the proposed methods are shown to enable adaptive measurement kernel design with high efficiency. Through the theoretical analysis and the simulation results, the proposed adaptive compressive detection methods are also demonstrated to provide significantly enhanced detection performance efficiently, compared to their counterpart with the conventional random measurement kernels.

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