Inversense software can always work by reading data obtained offline at mechanical tests. However, it is important for our customers who want to integrate the software into their structures and perform real-time and high-accuracy structural health monitoring for a long time, that the initial system installation is done correctly. In this installation package we offer, we meet all your needs for structural health monitoring and provide a ready-to-use system.

With this comprehensive installation package, we supply the optimum number of FBG sensors and interrogators according to the needs of your structures, decide how many sensors should be positioned, where and at what angles with our own optimization methods and place them, make the interrogator connections, and install the Inversense software and start real-time structural health monitoring, making your structures smart and alive. Afterwards, all you have to do is following the results produced by the Inversense software for you, carrying out your structural maintenance in the optimum time according to the regular reports it provides, and being informed immediately in case of an emergency such as damage prediction and take the necessary precautions.

Do you have existing sensors and interrogators in your company, but do you want to know how many sensors you should place at which angles and at which points of your structures and to perform structural health monitoring with minimum cost and maximum efficiency? The solution is at Mechanima!

We have sensor optimization methods to obtain high accuracy data at low cost during structural health monitoring. With these methods, we analyze structures and identify the points that really need sensor positioning with high accuracy. In order to monitor the health of all kinds of engineering structures in the most accurate way, we provide you with optimization analyses and guidance specific to your structure, eliminating the need to place sensors all over the structure and allowing you to perform highly efficient shape sensing with a small number of sensors.