# A Novel Hybrid Whale-Chimp Optimization Algorithm for Structural Damage Detection
## 1 Introduction  
Structures usually have a long service life. During their service period, the structural performance will continue to decline due to factors such as temperature changes, chemical erosion, and component aging [1]. Therefore, a timely and accurate assessment of the overall performance of the structure is essential to ensure the safety and long-term service of the building structures [2]. Structural health monitoring technology is used to evaluate the safety and durability of the structure during service to determine the service performance and remaining life of the structure [3, 4]. Structural damage detection based on structural properties is a core research topic in structural health monitoring. It has always been a hot topic in academic discussions and research [5, 6]. Many scholars have proposed various damage detection methods, which are mainly divided into the following two types: methods based on static characteristics and methods based on dynamic characteristics. Static characteristics of the structure can reflect the stiffness change of the structure more intuitively, which has been studied by many scholars. [PERSON] et al. [7] calculated the structural boundary conditions and material properties through the change of structural characteristics under static load, to achieve the goal of identifying the operating state of the structure. [PERSON] et al. [8] established an objective function for structural damage detection based on the change of static deflection andcarried out structural damage detection by solving the optimal value of the objective function. [PERSON] et al. [9] performed an inversion analysis of structures including shear effects based on vertical deflection data to identify structural damage. [PERSON] and [PERSON] [10] proposed a method to determine structural damage based on static response equations. [PERSON] [11] developed a method based on displacement curvature changes to identify structural damage. [PERSON] [12] proposed a strategy to identify structural damage based on the deflection change of bridges to update the finite element model. [PERSON] and [PERSON] [13] introduced a model-free structural damage detection method using static measurement data and modal interval analysis to detect damage. [PERSON] et al. [14] presented a method for structural damage detection of statically loaded structures based on the change of internal force and displacement of the finite element model. [PERSON] et al. [15] successfully identified the local damage of Euler-Bernoulli beams based on static loads and boundary conditions under the interference of environmental noise. However, these studies based on static characteristics still have some shortcomings, such as the cost being high and the response data being easily disturbed by external factors. Therefore, some researchers begin to pay attention to structural damage detection methods based on dynamic characteristics. Damage detection methods based on structural dynamic characteristics can be divided into damage detection methods based on dynamic fingerprints [16] and damage detection methods based on model updating [17]. The dynamic fingerprint methods, also known as the modal parameter method, use the modal parameters of the structure as damage factors of the structure, such as natural frequency [18; 19], mode shape [20; 21; 22], flexibility matrix [23; 24], modal curvature [25; 26] and modal strain energy [27; 28]. Usually, when a structural element is damaged, the stiffness of the corresponding element will change, and the modal information will also change. However, obtaining complete modal information for structures requires a large number of sensors, which is difficult to achieve in practical engineering. In addition, the dynamic fingerprint measurement process is easily affected by noise, which limits the development of such methods to a certain extent.