The development of sensor and system identification methods are making possible to detect modal parameters variations real-time and remotely. This area is commonly known as Structural Health Monitoring (SHM). Monitoring can be done locally at critical elements of a structure (strain, stress, displacements, etc.) or globally like dynamic parameters such as the natural frequency, damping and modal shapes. Structural monitoring allows the monitoring of the dynamic properties of the structure and their variations as well as the long-term performance of the structure by which the damage that could cause the structure out-of-service might be obtained. Response of the structure against severe earthquakes and winds and threshold values for relative displacements or drift ratios for life safety can be determined.So what's your need for matlab if for simulation i think simulink will be use.see example in attachment.
Outlier detection methods are a branch of data mining if computer science which can be used for structural health monitoring. Such methods detect anomalies in the data collected of structure state as damage candidates. There are many outlier detection algorithms such as statistical based, distance based, density based, clustering based and etc for the purpose of Outlier detection. The code of some these methods are available in Internet. Also, there are papers about health monitoring using anomaly detection algorithms which can be used as your solution.