Smart Structural Health Monitoring Using Finger Print Diagram of Frequency Response

Smart Structural Health Monitoring Using Finger Print Diagram of Frequency Response

The represented approach in the paper is based on monitoring of an expensive structure and provides exact location and size of the defect. By this mean, plus a statistical analysis in which probable locations of crack initiation are foreseen, wiser measures would be devised to resolve any problems through repairment and maintenance process. Damage detecting in many engineering societies is of great priorities because of the failures which leads to disasters with considerable financial damages and death toll out of damages and faults in structures and equipments. Airplane fall, bridge collapse, gas pipeline explosion are instances of these disasters. When a defect forms, it changes properties of the structure or the component against the dynamic excitations. These even slight changes lead to changes in natural mode shapes of the structure and its modal analysis response. Analytical, numerical or experimental Analysis of the Frequency Response Function (FRF) can leads us through diagnosing the sort of defect and its size By devising major algorithm in FEM modeling of the component and contribution of the damage influences in this analytical model, we can use it as a powerful tool for defect localization. Through FEM algorithm there are two important points, first modeling process which signifies a repetitive trend that leads to certain general trend. Second the accuracy we expect from the analytical method whereas levels of simplification is needed in modeling the defect and the generalized results are finally used to investigate the damages. In this paper we are mainly seeking an algorithm with which we become capable of localization the defect using a single smart material patch. After doing so many analysis we get to realize each sort of defect according to its location and size has got certain and unique modal behavior in a frequency domain in which even analysis on just one point of data acquisition can make us diagnose the sort of defect. In this method we need to first analyze a healthy component once and then attach a smart material patch which is a piezoelectric in the present work and find the defect and its location. In other papers we assumed three smart material patches and the analysis and comparison were made on the resulting data but in the present work we use the so-called finger print diagrams which are unique and do the analysis on defect specifications. Here we present a method based on assumption of a hole as a defect existing on a plate. This method is mostly used in expensive components like the ones in space shuttles or other similar sensitive equipments in which by attaching a single patch of smart material their health can be monitored.