Effective Performance Monitoring and Failure Diagnosis of Complex Systems- Sensor Placement Optimization

Optimal sensor selection helps provide more effective system health information from the perspective of economic and technical constraints. Optimization models confront different issues. For instance, many complex systems are inherently nonlinear, requiring nonlinear modeling. Optimization also confronts modeling uncertainties, as complex systems include human elements, and most importantly component interactions.

The interdependencies among system components and multiple failure modes present a challenge for system health diagnostics and prognostics. A reliable diagnosis and prognosis can only be ensured when all component conditions are monitored with minimum uncertainty. In this regard, sensors should be selected based on their priority in providing system health information.

Currently, most of the research on sensor optimization models optimize sensors position and orientation. However, the type of the sensors should be optimized as well. In the following studies, two different methods are proposed that optimize sensor location and type to achieve maximum information about system health status, considering budget and technical limitations.

Read More ...