With the advent of Internet of Things (IoT) a slow shift is happening from manual checks of capital intensive assets such as bridges, wind turbines, etc., where bolted joint is used as a main fastening method, towards unattended Structural Health Monitoring (SHM). Numerous approaches are proposed for monitoring the looseness of bolted joint assemblies, however, the majority of them can only be used for looseness detection purposes and not viable for monitoring since these approaches contain design impracticalities, not scalable or hard to implement outside of the laboratory environment. Furthermore, remote unattended monitoring is still very much in its infancy. Thus, to solve this issue, we propose a TenSense M20, a custom designed smart sensor node for continuous remote SHM of bolted joints. Complete node design is presented. Each aspect of the design is evaluated both by simulation and practical tests. Long Range (LoRa) is used as a means of wireless communication and the network can cover 3.8 km. The results show that TenSense M20 is able to precisely track the pre-tension force of a bolted joint with the approach being robust and scalable. Several transmission scenarios are analyzed and in the worst case scenario the node is estimated to last more than 5 years powered by several LiSOCl2primary batteries. Received data is securely stored in a blockchain and is easily accessible for services targeting integration with a Smart City.
Load monitoring and damage identification are important tasks in the field of Structural Health Monitoring. Reconstructing unknown force inputs or system parameters usually involves the solution of an inverse problem which is mostly ill-posed. In the last decades a lot of effort has been spent in solving these problems separately. However, unknown loads and damage both have influence on the structural vibration pattern. The difficulty of simultaneous identification of external forces and structural damage is to distinguish these influences by using only the measured vibration effects. The use of prior knowledge of the unknown quantities is advisable for solving the combined inverse problem and to obtain meaningful solutions. In this contribution a sparsity-based reconstruction method in time domain is developed for identifying the unknown structural force excitation and damage parameter simultaneously by using output-only acceleration data. Sparsity means the majority of the solution vector is zero and only a very few elements are nonzero. Here damage is interpreted as additional load on the damaged structural element (virtual distortion). A numerical proof-of-concept experiment of a quadratic aluminum plate is presented. It shows that the proposed reconstruction method is able to identify the unknown external force and damage parameter by using a significant lower number of accelerometers than present methods.
In this paper we consider the mathematical model of thermo- and photo-acoustic tomography for the recovery of the initial condition of a wave field from knowledge of its boundary values. Unlike the free-space setting, we consider the wave problem in a region enclosed by a surface where an impedance boundary condition is imposed. This condition models the presence of physical boundaries such as interfaces or acoustic mirrors which reflect some of the wave energy back into the enclosed domain. By recognizing that the inverse problem is equivalent to a statement of boundary observability, we use control operators to prove the unique and stable recovery of the initial wave profile from knowledge of boundary measurements. Since our proof is constructive, we explicitly derive a solvable equation for the unknown initial condition. This equation can be solved numerically using the conjugate gradient method. We also propose an alternative approach based on the stabilization of waves. This leads to an exponentially and uniformly convergent Neumann series reconstruction when the impedance coefficient is not identically zero. In both cases, if well-known geometrical conditions are satisfied, our approaches are naturally suited for variable wave speed and for measurements on a subset of the boundary.