# Effect of Environmental Parameters on Structural Health Status Assessment Using OMA Techniques
## 1 Introduction  
Structural health monitoring (SHM) is the process of checking the condition of a structure through an automated monitoring system. SHM techniques started in aerospace and automotive fields, but due to their multidisciplinary nature and potential, in the last decades they are widely used and adapted for civil engineering. In an SHM process, the data acquisition can be carried out periodically, or as is more common in recent years, continuously. In this second case, the volume of sampled data may be not negligible, and therefore advanced data management skills are needed [1, 2]. The objectives of SHM can be divided into the following five levels [2, 3]:  
1. Damage detection: giving a qualitative indication of the probable presence of damage in the monitored system. 2. Damage localization: giving an information about the probable location of the damage in the monitored system. 3. Damage classification: giving an information about the possible type of damage. 4. Damage assessment: giving an estimate of the probable extent of damage. 5. Damage prognosis: giving information on the structural safety, e.g., estimating the useful life of the structure after damage. High-order levels generally require the information necessary to determine the lower order levels. The first two levels will be investigated in this work for the monitoring of the examined system. The development of an SHM-based method generally depends on two key factors: the technology of the sensor used for monitoring, and the algorithm used for the interpretation of sampled signals. A structural monitoring system generally consists of several key components: sensors, data acquisition, data transmission, data processing, data storage, and structural health assessment [2]. Each of these phases plays a key role. The following work will examine the stages of data processing and health assessment. Strategies for monitoring the health status of a structure can be categorized into two main groups that generally provide different types of information [2]: global monitoring and local monitoring. The most appropriate type of monitoring depends on the kind of structure. For example, a global approach should be chosen when access to specific parts of the structure is impossible [2]. For a global monitoring system, accelerometers are one of the most-used type of sensors. The measurement of acceleration data can be used to estimate the modal parameters of the system and damage can be investigated by evaluating their variation over time. In this paper, a global approach was used. Two aluminum rods are monitored by means of a network of accelerometers. A series of simulated damages of different magnitudes were simulated in different positions of the rods by adding small masses. The modal parameters of the system were derived using different OMA techniques. The raw modal parameters were cleaned of environmental thermal effects to separate the effect of environmental disturbance parameters from the effect of the damage. The effectiveness of the applied OMA methods and the limits of the monitoring system were evaluated, studying the capacity for detecting the variation of the modal parameters due to applied damage without being blinded by the ambient disturbances. OMA techniques have been studied for years and are well established nowadays. In recent years, many studies have been conducted on automatic OMA techniques that allow the automatic identification of modal parameters. These techniques are particularly suitable in continuous monitoring situations over long periods [4; 5; 6]. However, there has never been enough focus on the aspects that can influence the interpretation of dynamic identification results. In fact, the dynamic behavior of most types of structure is strongly influenced by the environmental conditions in which the structure operates. The influence of environmental conditions can mislead the assessment of the health status of the structure. Therefore, their influence on the modal parameters must be studied very carefully.