As pointed out in the previous part, it is an important goal to design and construct safe, ecological and reliable structures, which are still cost effective. In order to guarantee these requirements, especially in industries where the component reliability is crucial, regular inspection intervals must be defined. As traditional inspection techniques can be very expensive in terms of both man hours and structure down-time, the development of suitable automatic and reliable monitoring methods, which can be used on demand, would be very valuable. This requires techniques which can monitor the given structure either continuously or in fixed intervals and can provide suitable early warning before a propagating damage reaches the limits of criticality. Here is the place where structural health monitoring systems enter into play. To perform these tasks, a monitoring system should decide autonomously whether the host structure is damaged or not. On that account the article “Damage Identification using Nonlinear Data-Driven Modelling – Methodology” of this book describes the methodology of a novel data driven approach based on scale-frequency analysis, multiway hierarchical nonlinear principal component analysis (h-NLPCA), squared prediction error statistic (SPE) and self-organizing maps (SOM) for the detection and classification of damage in structures. In this article the application of this approach is described in detail for two case studies, a metallic pipeline and an aircraft composite skin panel. This article, which contains the experimental results of the proposed method, is organized as follows: First, a very short summary of the proposed methodology is given in the section “Theoretical Background”. Afterwards the application of this method is shown in detail within an experimental evaluation for two samples made from different materials. Their analysis is followed by the discussion of the results. Finally, concluding remarks are given in the last section. Miguel Angel Torres Arredondo MAN Diesel and Turbo SE, Germany