Design of High Sensitivity Foreign Object Detection System in Wireless Charging Based on the Variation of Detection Coils Impedance

2021 ◽  
pp. 775-789
Author(s):  
Ying Sun ◽  
Jixing Liu ◽  
Ce Liang ◽  
Guo Wei ◽  
Chunbo Zhu ◽  
...  
Keyword(s):  
Object Detection ◽  
Detection System ◽  
High Sensitivity ◽  
Wireless Charging ◽  
Foreign Object

scholarly journals Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Hyperspectral Imaging ◽  
High Speed ◽  
Detection System ◽  
Imaging Techniques ◽  
Foreign Object ◽  
Subtraction Method ◽  
Foreign Objects ◽  
Time Operation

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

scholarly journals A Novel Metal Foreign Object Detection for Wireless High-Power Transfer Using a Two-Layer Balanced Coil Array with a Serial-Resonance Maxwell Bridge

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2070
Author(s):  
Sunhee Kim ◽  
Haeyong Jung ◽  
Youngjun Ju ◽  
Yongseok Lim
Keyword(s):  
Object Detection ◽  
High Power ◽  
Bridge Circuit ◽  
Detection System ◽  
Transmission Efficiency ◽  
Foreign Object ◽  
Power Transfer ◽  
Coil Array ◽  
Foreign Objects ◽  
Change Detection Performance

In a wireless high-power transfer system with a distance of several tens of centimeters apart between the transmitter and receiver coils, one of the most challenging issues is to detect metallic foreign objects between the transmitter and receiver coils. The metallic foreign objects must be detected and removed since these reduce the transmission efficiency and cause heat generation of the transmitter and receiver. This paper presents two-layer symmetric balanced coil array so that if there are metallic foreign objects, it can be detected through the change of the inductance of the balanced coils. Since the balanced coil is composed of coils that are in a symmetrical relationship in position, there is no need for a reference coil, and interference between coils is reduced by dividing the coil into two layers. In addition, a novel serial-resonance Maxwell bridge circuit to improve the inductance change detection performance is presented in this paper. The proposed metallic foreign object detection system is implemented using two-layer balanced coil array with a serial-resonance Maxwell bridge and the experimental results show that voltage changes of hundreds of mV to several V occur when a metallic foreign object is inserted, so that even small metals such as clips can be detected.

scholarly journals Foreign Object Detection for Electric Vehicle Wireless Charging

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 805
Author(s):  
Jinglin Xia ◽  
Xinmei Yuan ◽  
Jun Li ◽  
Sizhao Lu ◽  
Xinxu Cui ◽  
...  
Keyword(s):  
Object Detection ◽  
Electric Vehicle ◽  
Detection Methods ◽  
Wireless Charging ◽  
Foreign Object ◽  
Wireless Power ◽  
Unified Framework ◽  
Metal Object ◽  
Safety Requirements ◽  
Future Challenges

Wireless power transfer technology is being widely used in electric vehicle wireless-charging applications, and foreign object detection (FOD) is an important module that is needed to satisfy the transmission and safety requirements. FOD mostly includes two key parts: metal object detection (MOD) and living object detection (LOD), which should be implemented during the charging process. In this paper, equivalent circuit models of a metal object and a living object are proposed, and the FOD methods are reviewed and analyzed within a unified framework based on the proposed FOD models. A comparison of these detection methods and future challenges is also discussed. Based on these analyses, detection methods that employ an additional circuit for detection are recommended for FOD in electric vehicle wireless-charging applications.

scholarly journals Transcription Alignment of Historical Vietnamese Manuscripts without Human-Annotated Learning Samples

2021 ◽  
Vol 11 (11) ◽  
pp. 4894
Author(s):  
Anna Scius-Bertrand ◽  
Michael Jungo ◽  
Beat Wolf ◽  
Andreas Fischer ◽  
Marc Bui
Keyword(s):  
Object Detection ◽  
State Of The Art ◽  
Positive Impact ◽  
Detection System ◽  
Training Data ◽  
Detection Accuracy ◽  
Current State ◽  
Alignment Task ◽  
Scanned Image ◽  
Automatic Transcription

The current state of the art for automatic transcription of historical manuscripts is typically limited by the requirement of human-annotated learning samples, which are are necessary to train specific machine learning models for specific languages and scripts. Transcription alignment is a simpler task that aims to find a correspondence between text in the scanned image and its existing Unicode counterpart, a correspondence which can then be used as training data. The alignment task can be approached with heuristic methods dedicated to certain types of manuscripts, or with weakly trained systems reducing the required amount of annotations. In this article, we propose a novel learning-based alignment method based on fully convolutional object detection that does not require any human annotation at all. Instead, the object detection system is initially trained on synthetic printed pages using a font and then adapted to the real manuscripts by means of self-training. On a dataset of historical Vietnamese handwriting, we demonstrate the feasibility of annotation-free alignment as well as the positive impact of self-training on the character detection accuracy, reaching a detection accuracy of 96.4% with a YOLOv5m model without using any human annotation.

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