Health Monitoring of an Auxiliary Power Unit Using a Classification Tree
The objective of this work is to present a method to monitor the health of Auxiliary Power Units (APU) using a Dynamic Computational Model, Gas Path Analysis and Classification and Regression Trees (CART). The main data used to train the CART consists of measurements of the exhaust gas temperature, the bleed pressure and the fuel flow. The proposed method was tested using actual APU data collected from a prototype aircraft. The method succeeded in classifying several relevant fault conditions. The few misclassification errors were found to be due to the insufficiency of the information content of the measurement data. *
Predictive Maintenance Optimization for Aircraft Redundant Systems Subjected to Multiple Wear Profiles
Researchers and industry practitioners have recently demonstrated great interest in maintenance planning since it directly impacts the lifecycle cost and availability of systems. Considering the aviation industry, this impact is even more relevant due to high-availability expectations from aircraft operators and high costs incurred when an aircraft becomes out of service. For this reason, some minor maintenance activities are carried out near the gate, between two consecutive flight legs. These activities are referred to as aircraft line maintenance. The usage of prognostics and health management techniques may help the prevention of unexpected events when caused by degrading components. The application of prognostics techniques together with a line maintenance planning optimization approach is not a trivial task and requires sophisticated mathematical approaches especially when dealing with complex and integrated systems. This paper proposes a methodology for predictive line maintenance optimization of redundant aeronautical systems subjected to multiple wear conditions. Degradation trends and future wear values are estimated considering an implementation of a multiple model approach of the extended Kalman filter technique. Planning optimization is based on the minimization of operational costs comprising several aspects of the aviation industry such as dispatch requirements, delays, cancellations, and equipment costs. A case study is conducted using field prognostics data of hydraulic systems to evidence the efficiency and benefit of the proposed methodology.
Lake Muzahi, Rwanda: limnological features and phytoplankton production
Lake Muhazi, a small lake of Rwanda (East Africa) was studied from 1986 to 1990. A dramatic decrease of the catch of Oreochromis niloticus (350 T y−1 in the fifties vs 30 T y−1 in 1982) suggested a loss of productivity or overfishing. In the same period, other ecological changes occurred: the submerged macrophytes regressed and there was a decrease in Secchi depth (0.65 m in 1987 vs 1.5 m in the fifties). Compared to other lakes of the same area, the plankton production seemed low. The results of the present study characterize lake Muhazi as a shallow lake with a rather unstable diurnal stratification and with slight differences in mixing regime between its eastern, deepest part and its western, shallowest part. Secchi disk depth does not vary seasonally to a large extent. The water has a rather high mineral content (conductivity of about 500 µS cm−1 at 25 °C) and low concentrations of dissolved N and P, except in the hypolimnion, where NHinf4sup+-N can be high.Two species, Microcystis aeruginosa and Ceratium hirundinella, account for most of the phytoplankton biomass, which is about 50–80 mg chlorophyll a m−2 in the euphotic zone, usually with little seasonal variation. Daily gross production estimates amount to about 6 to 9.5 g O2 m−2 d−1 with a significant difference between the two parts of the lake. Data on C:N and C:P ratio in the phytoplankton suggest that some N deficiency might occur in the eastern part. Moreover, the Zm:Zc ratio could also lead to rather low net production rates (0.21–0.25 d−1 for a mixed layer of 4 m)In conclusion, the primary production of lake Muhazi is medium for African lakes and the hypothesis that decreased planktonic production could account for a reduced fish production should be discarded. Whereas the present yield of the fishery is only 20 kg ha−1 y−1, the yield estimated from primary production ranges between 46 and 64 kg ha−1 y−1. This could be reached through proper management. Finally, some hypotheses are given to explain the ecological changes which occurred in the lake.