A modular intelligent data administration approach for helicopter health and usage monitoring systems

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A modular intelligent data administration approach for helicopter health and usage monitoring systems

Azzam, H. / Andrew, M.

Much effort and expenditure has been focused on the introduction of acquisition and processing hardware for helicopter health and usage monitoring systems (HUMS) operations. In contrast, the potential difficulties in the management of HUMS data have received much less attention. HUMS hardware will typically generate in excess of one megabyte of data per flight. This data will be down-loaded to ground station computer for further analysis. A modular intelligent data administration system (MIDAS) is highly desirable in order to efficiently extract useful information from the huge amount of HUMS data, and provide general robust diagnostic strategies. A state-of-the-art implementation of relevant technologies and analysis methods is essential to realize such a system. This paper presents the requirements and structure of MIDAS and details an approach that integrates neural network technology, helicopter mathematical dynamic models and unsupervised pattern recognition techniques. Examples using vibration and spectrometric oil analysis programmes (SOAP) as a means to evaluate the health and usage of helicopter components are presented.