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A Semi-Supervised Siamese Network for Complex Aircraft System Fault Detection with Limited Labeled Fault Samples

Xinyun Zhu, Sun Jianzhong, Hu Hanchun, Li Chunhua

Eksploatacja i Niezawodność

2023

Vol. 25, no. 4

art. no. 174382

Health monitoring and fault detection of complex aircraft systems are paramount for ensuring reliable and efficient operation. The availability of monitoring data from modern aircraft onboard sensors provides a wealth of big data for developing deep learning-based fault detection methods. However, aircraft onboard systems typically have limited labeled fault samples and large amounts of unlabeled data. To better utilize the information contained in limited labeled fault samples, a deep learning-based semi-supervisedfault detection method is proposed, which leverages a small number of labeled fault samples to enhance its performance. A novel sample pairing strategy is introduced to improve algorithm performance by iteratively utilizing fault samples. A comprehensive loss function is employed to accurately reconstruct normal samples and effectively separate fault samples. The results of a case study using real data from a commercial aircraft fleet demonstrate the superiority of the proposed method over existing techniques, with improvements of approximately 16.7% in AP, 9.5% in AUC, and 19.2% in F1 score. Ablation studies confirm that performance can be further improved by incorporating additional labeled fault samples during training. Furthermore, the algorithm demonstrates good generalization ability.

Application of chromatographic plate theory on the weathered crust elution-deposited rare earth ore with carboxylate

Zhang Zhenyue, Wang Guangshuai, Li Chunhua, Chi Ruan, Long Fei, Chen Zhuo, Chi Xiao Wang, Liu Defeng

Physicochemical Problems of Mineral Processing

2021

Vol. 57, iss. 4

48--62

To improve the leaching process of rare earth and reduce the impurities in the leachate, the carboxylate ammonium, such as ammonium acetate, ammonium citrate and ammonium tartrate, were selected as lixiviant to compare the effects of concentration, flow rate, pH and temperature on leaching mass process of rare earth and aluminum. Meanwhile, the leaching behaviors of rare earth and aluminum leached by three kinds of carboxylate ammonium were analyzed by chromatographic plate theory. The relationship between the flow rate and height equivalent (HETP) could fit well with the Van Deemter equation and there was an optimal flow rate (uopt) for the leaching of the rare earth and aluminum. Besides, the conditions of carboxylate ammonium lixiviant were optimized. The optimum concentrations of ammonium acetate, ammonium tartrate and ammonium citrate were 15 g/L, 25 g/L and 5 g/L respectively, the leaching flow rate was 0.50 mL/min, the pH value was approximatively 7.00 and the leaching temperature was 293 K to 303 K. At these conditions, the mass transfer efficiencies of three ammonium carboxylates for rare earth and aluminum was in the order of ammonium acetate > ammonium tartrate > ammonium citrate. Moreover, the ammonium acetate could commendably inhibit aluminum ions entering the lixivium.