Delve into the theoretical frameworks and computational models used in structural health monitoring $($SHM$)$ for assessing the condition and performance of civil engineering structures over time. Discuss the underlying principles of SHM techniques such as vibration$-$based monitoring, acoustic emission analysis, and non$-$destructive testing, and examine their applicability in detecting, diagnosing, and mitigating structural defects, fatigue, and deterioration. Evaluate the role of advanced sensing technologies, data analytics, and machine learning algorithms in enhancing the effectiveness and reliability of SHM systems for ensuring the safety and resilience of critical infrastructure assets.