Intelligent Automation, Incorporated (IAI) and its subcontractor, Penn State U., propose a novel system to detect damage in aircraft structures. The system combines novel TFT based thin film actuators and sensors for signal acquisition and a robust software for fault prognosis and diagnosis. The actuator/sensor is known as PVDF-IDT (Polyvinylidine Fluoride Interdigital Transducer) that is integrated into a TFT switching circuit. It is low cost, compact, flexible, and has great potential for wireless interrogation. PVDF-IDT sensor has been proven to be useful for sensing cracks in rivet holes as well as other structural defects such as corrosion, delamination, and fatigue cracking. The second element of the system is an automatic fault prognosis tool, which consists of Principal Component Analysis (PCA), Learning Vector Quantization (LVQ), and Hidden Markov Model (HMM). PCA is a popular neural network tool for extracting useful features. LVQ is used to generate the code sequence. HMM has been proven to be extremely useful in several applications, however, HMM is used here to perform both fault prognosis and diagnosis. Our proposed system can perform continuous monitoring of aircraft structures in both ground and in-flight situations, and the sensors can be easily embedded into the structure.