A Review on Optimal Sensor Placement for Health Monitoring
Sensor data provide the foundation for performance and health assessment of most complex systems. An optimal sensor placement is defined as a sensor configuration that achieves the minimum cost while observing prespecified performance criteria. Various optimization algorithms, from random search to heuristic algorithms, have been used for optimizing the sensor placement. A literature search for sensor placement methods yields a large number of publications on various optimization methods. Random search is suitable for a small and simple sensor placement problem since it is straightforward and easily implemented. But it is time consuming and inefficient when dealing with a large system. A variety of heuristic search methods, including Simulated Annealing, Tabu Search, or Genetic Algorithms are available. In large-scale systems consisting of multiple components, a fault may propagate through several components when it occurs. So the solution of sensor placement problem at the system level is required. Then Cause-Effect analysis methods, such as fault tree method, Petri-Net method, and graph theory, were widely used.
sensor placement optimal approach health monitoring GA DG
Liao CanXing Li Xingshan Zhang Ping Dai Jing
School of Automation Science and Electrical Engineering,BUAA,Beijing 100083 China
国际会议
西安
英文
2007-08-16（万方平台首次上网日期，不代表论文的发表时间）