The Optimal Mars Entry Guidance with External Disturbance Using Neural Network Solution

Li, Maomao; Guo, Ruike

doi:10.1007/978-981-32-9050-1_59

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B Training and Test Dataset Generation1

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2019

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“…In order to ensure the reliability of the diagnosis results, it is necessary to normalize all the input parameters. We adopt the min-max normalization method as shown in (5) [28].…”

Section: B Training and Test Dataset Generationmentioning

confidence: 99%

Deep Belief Network-Based Gas Path Fault Diagnosis for Turbofan Engines

Liu

Wang

et al. 2019

IEEE Access

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A gas path fault diagnosis scheme for turborfan engines based on deep belief network (DBN) is presented. The scheme is constructed according to the diagnosis principles of gas path faults and is composed of a turbofan engine reference model and a DBN diagnosis model. The DBN diagnosis model is a stacked network of several restricted Boltzmann machines (RBM) and was trained with the contrastive divergence algorithm and the back propagation algorithm. To optimize the DBN performance, the orthogonal tests L 25 (5 7) were adopted to determine the hyper-parameters, such as learning rate, hidden layer number, hidden layer neuron number, etc. The proposed DBN-based scheme was applied to diagnose the gas path faults of a turbofan engine model and compared with BP-based and SVM-based schemes. The results show that the fault diagnosis accuracy of the DBN-based scheme is as high as 96.59%, and the DBN-based scheme has dramatic performance advantages over the other two schemes. INDEX TERMS Turbofan engine, gas path, fault diagnosis, deep belief network, orthogonal test.

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“…In order to ensure the reliability of the diagnosis results, it is necessary to normalize all the input parameters. We adopt the min-max normalization method as shown in (5) [28].…”

Section: B Training and Test Dataset Generationmentioning

confidence: 99%

Deep Belief Network-Based Gas Path Fault Diagnosis for Turbofan Engines

Liu

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

The Optimal Mars Entry Guidance with External Disturbance Using Neural Network Solution

Cited by 1 publication

References 6 publications

Deep Belief Network-Based Gas Path Fault Diagnosis for Turbofan Engines

Deep Belief Network-Based Gas Path Fault Diagnosis for Turbofan Engines

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