# Hammering Test for Tile Wall Using Deep Learning
## 1 Introduction  
The aging of various social infrastructures and buildings has become a problem in recent years. So, the demand for infrastructure inspection services is increasing. This trend highlights the growing necessity for thorough assessments and maintenance of our infrastructure systems to ensure their safety and functionality for the future. As the condition of these structures will continue to deteriorate, the need for specialized inspection services will likely continue to escalate, emphasizing the importance of proactive measures in infrastructure management. Infrastructure inspection encompasses a variety of maintenance and management tasks, with particular attention given to diagnosing structural integrity and assessing seismic resistance. For hard-to-reach areas, such as large bridges and the exterior walls ofhigh-rise buildings, inspection robots and drones are increasingly being used in place of traditional scaffolding [1]. While numerous methods exist for detecting hidden anomalies, such as those within concrete walls, including techniques like infrared inspection [2] and electromagnetic wave testing [3], the hammering test remains a widely employed method. This technique assesses the condition of the interior by analyzing the sound produced when the surface of the wall is struck with a hammer. The hammering test is a highly accurate and cost-effective inspection method; however, it requires the expertise of experienced inspectors to correctly distinguish abnormal sounds. Figure 1 illustrates the fundamental principle behind the hammering test. When a structure is in good condition, with no cracks or cavities, the sound produced by the hammer strike closely resembles an impulse response, characterized by higher frequencies. Conversely, if the structure has issues such as cracks or cavities, the resulting sound is prolonged, reverberating with lower frequencies, indicating potential problems with the integrity of the structure. The decline in the number of skilled inspectors is becoming a significant concern due to the aging of the workforce. Hammering tests are essential for inspecting two main types of structures: concrete constructions such as bridges and high-rise buildings and decorative tiles commonly found in condominium and low-rise buildings. The use of tiles as a form of decoration has a long history, dating back over 5000 years to the invention of pottery. Today, tiles continue to be a popular choice for exterior finishes, especially for apartment buildings, as they contribute to the aesthetic appeal of the structures. There are two predominant methods for attaching tiles to surfaces: the mortar-applied method and the adhesive-applied method. The use of mortar to attach tiles dates back to ancient times, including the Egyptian dynasty. However, mortar-based tile adhesion is prone to large-scale peeling, meaning that when tiles start to peel, they tend to detach over a wide area. To address this issue, adhesives with stronger bonding capabilities have been recommended, as they localize the peeling to smaller areas. While adhesives are already widely used in more than half of newly constructed tiled buildings in urban areas, their adoption in rural areas has been slower due to the higher costs associated with their use. Our research has focused on developing a method that enables even unskilled workers to perform hammering inspections efficiently by employing deep learning techniques to distinguish between different hammering sounds [4]. However, these efforts have so far been limited to inspecting tile walls adhered with mortar. When it comes to adhesive-backed tile walls, peeling tends to be confined to individual tiles rather than large areas. This is because the adhesive material dampens the sound and vibration caused by the peeling, making it difficult to detect through traditional sound inspection methods. Even experienced inspectors face challenges in making accurate judgments under these conditions.