Enhancing vibration analysis by embedded sensor data validation technologies

This paper discusses a Structural Health Monitoring framework developed for aircraft airframes, where the objective is high performance vibration-based diagnostics using validated data from low power and miniaturized smart sensors. Although considerable research has been devoted to the structural health monitoring discipline, successful field implementations have not been widely achieved. This research presents a new embedded solution by integrating several state-of-the-art technologies. The system architecture is divided into two levels, with the low level built on embedded smart sensors capable of: self-diagnostics; high performance data acquisition; advanced vibration analysis; embedded admittance measurements; elastic wave generation; and wireless communications. A key capability is sensor data validation using an electromechanical impedance method, where failures in piezoelectric transducer elements as well as damage to the host structure are detected. Then, at the next level is a computation system hosting a graphical user interface with visualization methods, a feature extraction toolset, and advanced artificial neural network diagnostics. The overall goal of this research effort was to develop a system architecture with smart sensors and intelligent processing to be deployed in aircraft for the detection and isolation of global and incipient failures.