To reduce maintenance costs while maintaining safety, different corrosion mitigation strategies have been utilized. In addition to new structural materials and advanced protective coatings, improved maintenance planning approaches, including Condition Based Maintenance (CBM) approaches, have seen growing use over the past decade. As a potential key component to CBM corrosion practices, corrosion sensors have received increased attention within the DoD. In this work, we discuss some generalized global findings based on a large scale sensor deployment at 10 different locations. In particular, comparisons between temperature, relative humidity, conductance, and corrosivity will be made.
To reduce maintenance costs while maintaining safety, different corrosion mitigation strategies have been utilized. In addition to new structural materials and advanced protective coatings, improved maintenance planning approaches, including Condition Based Maintenance (CBM) approaches, have seen growing use over the past decade. One goal of any Condition Based Maintenance (CBM) effort is to use all available on-aircraft data as well as field and depot-based maintenance information to align resources in a timely manner to ensure aircraft safety while reducing maintenance and repair costs. While many factors influence these costs, it is known that corrosion-related processes cost the Department of Defense (DoD) billions of dollars annually. However, there is no currently accepted means of providing real-time indicators of environmental severity that predictably influence corrosion damage and subsequent costs. As a result, corrosion sensors have received increased attention within the DoD as a potential key component to CBM practices.
A common approach to corrosion severity prediction is to use long-term averages of environmental parameters (such as relative humidity, temperature, and pollutants), geographic features (such as coastal proximity), and witness coupon corrosion rates of indicator materials to classify an environment into one of a small number of severity categories 1-5. However, recent work has revealed that brief changes in environmental conditions—even those lasting only a few hours—can significantly affect total corrosion damage, and long-term averages of environmental conditions are not sufficient to accurately predict cumulative corrosion damage 6-9. To more accurately measure the corrosion damage from these short-term events, corrosion sensors are becoming increasingly popular. The frequent acquisition of environmental and corrosion data with increased measurement sensitivity are attractive features that may provide the parameters needed to effectively incorporate corrosion related effects into CBM models.
