Sensor Optimization Selection Based on Fault Detectability and Trackability
Correctly selecting and reasonably arranging sensors are critical to high fidelity health assessment and low testing costs. A novel approach of sensor optimization placement for health monitoring based on fault detectability and trackability is proposed in this paper. Firstly, the requirements of sensor selection for health monitoring, the definitions and calculations of fault detectability and trackability are presented. Thus, a Sensor Optimization Selection Model (SOSM), whose objectives are to maximize the fault detectability and trackability and minimize cost of sensors, is built. Afterwards, an Adaptive Simulated Annealing Genetic Algorithm (ASAGA) is implemented to solve the SOSM. Finally, the real gearboxes and experimental data are used to verify the effectiveness of the SOSM proposed in this paper and its solution. The results from this study have shown that the approach can provide a better strategy for health monitoring in order to reduce the test cost, improve the reliability and the capability.
Health monitoring Sensor Optimization Selection Model (SOSM) Adaptive Simulated Annealing Genetic Algorithm (ASAGA)
Luo Jianlu Tan Xiaodong
Officers College of PAP, Chendu610213, China
国际会议
重庆
英文
953-957
2015-12-18（万方平台首次上网日期，不代表论文的发表时间）