Fiber Bragg Grating (FBG) sensors are widely used to measure various physical parameters; such as liquid level, weight, temperature, vibration, etc. They are also used in structural health monitoring systems and environmental conditions.
Structural deformations are one of the most significant factors that affect machine tool (MT) positioning accuracy. These induced errors are complex to be represented by a model, nevertheless, they need to be evaluated and predicted in order to increase the machining performance. The solution is based on the use of a multiplexed optical fiber sensor with a sufficient number of Bragg gratings for strains measuring embedded in the structure. The high sensitivity of the sensors ( 0.2 με ) suggests to employ them in the MT with high stiff structures. FBG sensors are suitable to measure both strains and temperature with very high accuracy and resolution. FBG sensors may offer many advantages since they ensure a dynamic performance up to 260 Hz, permitting the exposure and measurement of distortions acting during the working operations. The determination of the tooltip displacement is a complex process if it is directly extrapolated from the strains. For this reason, it is more convenient to employ FBG as a displacement sensor and to measure the overall integral effect of some critical point-to-point dimensions of the MT geometry.
The conventional approaches are based on models able to predict the MT deformations, studying a relationship between machine accuracy and undesired loads. Nevertheless, it is difficult to identify a general robust relation and these models need to be calibrated for every machine variant limiting their success, increasing costs, and the implementation time. In the first part of the experimental tests, the model was validated by applying a set of static loads. This analysis showed a good match between the real and the predicted position of the MT tool tip point. In the same way, the tests were replicated varying the environmental temperature over time. Scientists highlight the significant advantages of applying FBG sensors in MT calibration such as their high sensitivity, geometrical versatility, lightweight, immunity to electromagnetic interference or chemical agents, high durability. Nevertheless, it also underlines the limits of this method. In particular, the accuracy of the model depends on the number and the position configuration of the sensors implemented in the structure. The choice of specific statistical methods may improve the accuracy of the model. In light of these results, the next steps of the research will be based on the fabrication of new prototypes changing the position configuration of the FBG sensors.