Multi Channels Data Fusion Algorithm on Quantum Genetic Algorithm for Sealed Relays

作者：Xin Qian, Shujuan Wang, Chao Li, Guotao Wang · 发表于：Journal of Physics Conference Series · 年份：2019 · DOI：10.1088/1742-6596/1237/2/022130 · 被引用次数：4 · 研究领域：Advanced Algorithms and Applications、Advanced Decision-Making Techniques、Target Tracking and Data Fusion in Sensor Networks

Abstract Particle Impact Noise Detection (PIND) is a screening test that must be done before the sealed relay is released. PIND signals are mostly occasional weak, which are difficult to measure and identify. In this paper, the three channel sensor is used to detect the remainder signals, and the weak signal is enhanced by weighted data fusion. For the first time, quantum genetic algorithm (QGA) is used to self-adaptively configure the weight, taking the place of arti-ficial settings. Experiments show that after data fusion, and the variance is only about 20% of the single input signal, which verifies the effectiveness of the algorithm. The computational complexity of QGA is offered.