Electromagnetic-Based Localization of Moisture Anomalies in Grain Using Delay-Multiply-and-Sum Beamforming Technique
Source abstract
Abstract
Timely detection and treatment of moisture anomalous regions in grain storage facilities is crucial for preventing mold growth, germination, and pest infestation. To locate these regions, this paper presents a novel anomalous moisture region localization algorithm based on the delay-multiply-and-sum (DMAS) beamforming techniques, including the design of an effective spatial arrangement of electromagnetic wave transmitters and receivers, along with comprehensive testing of detectable regions and experimental validation of anomaly localization across varying moisture levels and positions within grain piles. Following initial localization using the proposed algorithm, the study introduces a reliability assessment method for unknown samples based on the signal-to-mean ratio (SMR) value and compares the region of maximum response intensity with that of maximum connected domain volume. The system demonstrated successful localization of a 7 cm × 7 cm × 7 cm region with 15.4% moisture content within a cubic experimental bin containing 10.5% moisture content long-grained rice, achieving an average recall accuracy exceeding 50%. The proposed method presents rapid detection capabilities and precise localization, showing potential for moisture content evaluation of anomalous regions and practical applications in grain storage monitoring systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ultrasonics and Acoustic Wave Propagation · Non-Destructive Testing Techniques · Geophysical Methods and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Guangzhou Institute of Advanced Technology, Guangzhou 511458, China
National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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