Optimising Sensor Placement in Structural Health Monitoring for Anomaly Detection

Structural Health Monitoring systems play a critical role in ensuring the safety and longevity of infrastructure by continuously assessing the structural integrity in a timely manner. Effective monitoring relies heavily on the optimal placement of accelerometer sensors, as too many sensors increase costs while insufficient sensors may compromise anomaly detection. The final goal is to provide reliable, high-resolution insights into the health of complex infrastructures, and a standardized methodology to guide future structural health monitoring projects in developing cost-effective and accurate sensor layouts for critical infrastructure, considering both the type of structure and the environmental conditions. This paper presents a data-driven methodology structured around the Deming cycle (Plan-Do-Check-Act) to optimise sensor placement. The proposal aims to minimise the number of accelerometers while maintaining high detection accuracy and spatial coverage for structural anomaly identification. The validation is conducted by applying the proposal to the Z24 bridge dataset, a well-known benchmark from a box girder bridge in Switzerland, which contains detailed vibration responses under progressive damage conditions. The proposed approach results in a sensor reduction of over 89.61% without losing sensitivity to structural anomalies. This demonstrates the effectiveness and practicality of the Deming cycle methodology for real-world structural health monitoring applications, providing significant cost savings and improved monitoring efficiency.