The military spends billions of dollars annually on inspection and repair of damage resulting from corrosion of high value assets, including aircraft and support equipment. Currently available methods for identifying and preventing corrosion involve labor intensive scheduled inspections and maintenance that are costly and reduce asset availability. In order to increase overall safety, availability, and operational efficiency, an online monitoring system capable of fusing data streams from an array of environmental and corrosivity sensors has been developed. The sensing system has been designed to provide autonomous indications of corrosive severity throughout an airframe. The sensors, system design, and corrosivity classification methods are detailed. Results and analysis of the wireless, ultra-low power sensor network performance in laboratory tests and vehicle service environments are given. By providing a high level of visibility for corrosion within a structure the system can be used to improve asset management for corrosion prevention and control.

Localized corrosion process such as pitting, crevice corrosion, exfoliation, and environment assisted cracking are difficult to detect and can significantly degrade structural integrity. A corrosion monitoring system that includes various environmental and corrosivity sensors is used to track component environmental exposure as a function of time. Corrosion diagnostic models based on measurements of exposure conditions, corrosion rate, and cumulative environmental severity can be embedded into the system for real-time corrosion evaluation. For given future environmental conditions, these models can be used to forecast and schedule inspection and maintenance activities.

The system provides a clear indication of environmental severity, exposure conditions, and corrosion rates within a structure, and the embedded models contained within the system can provide maintainers direct access to understandable and actionable information. These capabilities allow for increased efficiencies in maintenance practices, leading to lower life cycle costs and increased asset availability.

Subject
Humidity, Time of wetness, Electrochemical impedance spectroscopy, Sensors, Corrosion rate, Aircraft, Corrosivity, Sodium chloride, Sodium chloride solution, Corrosion data, Corrosion resistance, Relative humidity, Surface temperature
Keywords:
Corrosion sensors, structural health monitoring, condition based maintenance, diagnostics, prognostics
© 2013 Association for Materials Protection and Performance (AMPP). All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of AMPP. Positions and opinions advanced in this work are those of the author(s) and not necessarily those of AMPP. Responsibility for the content of the work lies solely with the author(s).
2013
Association for Materials Protection and Performance (AMPP)
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