Aeroengine Fault Diagnosis Method Based on Optimized Supervised Kohonen Network

To diagnose the aeroengine faults accurately,the supervised Kohonen(S-Kohonen)network is proposed for fault diagnosis.Via adding the output layer behind competitive layer,the network was modified from the unsupervised structure to the supervised structure.Meanwhile,the hybrid particle swarm optimization(H-PSO)was used to optimize the connection weights,after using adaptive inheritance mode(AIM)based on the elite strategy,and adaptive detecting response mechanism(ADRM),HPSO could guide the particles adaptively jumping out of the local solution space,and ensure obtaining the global optimal solution with higher probability.So the optimized S-Kohonen network could overcome the problems of non-identifiability for recognizing the unknown samples,and the non-uniqueness for classification results existing in traditional Kohonen(T-Kohonen)network.The comparison study on the GE90 engine borescope image texture feature recognition is carried out,the research results show that:the optimized S-Kohonen network has a strong ability of practical application in the classification fault diagnosis;the classification accuracy is higher than the common neural network model.

An Improved Biometric Fuzzy Signature with Timestamp of Blockchain Technology for Electrical Equipment Maintenance

The power infrastructure of the power system is massive in size and dispersed throughout the system.Therefore,how to protect the information security in the operation and maintenance of power equipment is a difficult problem.This paper proposes an improved time-stamped blockchain technology biometric fuzzy feature for electrical equipment maintenance.Compared with previous blockchain transactions,the time-stamped fuzzy biometric signature proposed in this paper overcomes the difficulty that the key is easy to be stolen by hackers and can protect the security of information during operation and maintenance.Finally,the effectiveness of the proposed method is verified by experiments.

Co-synthesis of vertical graphene nanosheets and high-value gases using inductively coupled plasma enhanced chemical vapor deposition

One-step controllable synthesis of vertical graphene nanosheets （VGs） and high-value gases was achieved using inductively coupled plasma enhanced chemical vapor deposition （ICPECVD）. The basic physical properties of the ICPECVD process were revealed via electrical diagnosis and optical emission spectroscopy. The coil current and voltage increased linearly with the augmenting of injected power, and CH, C2, H2 and H were detected at a wavelength from 300 to 700 nm, implying the generation of abundant graphene-building species. The morphology and structure of solid carbon products, graphene nanosheets, were systemically characterized in terms of the variations of operating conditions, such as pressure, temperature, gas proportion, etc. The results indicated that an appropriate operating condition was indispensable for the growth process of graphene nanosheets. In the present work, the optimized result was achieved at the pressure, heating temperature, applied power and gas proportion of 600 mTorr, 800 ~C, 500 W and 20：20：15, respectively, and the augmenting of both CH4 and H2 concentrations had a positive effect on the etching of amorphous carbon. Additionally, H2 and C2 hydrocarbons were detected as the main exhaust gases. The selectivity of H2 and C2H2, measured in exhaust gases, reached up to 52% and 8%, respectively, which implied a process of free radical reactions and electron collision dissociation. Based on a comprehensive investigation of spectral and electrical parameters and synthesized products, the reaction mechanism of collision, dissociation, diffusion, etc, in ICPECVD could be speculated, providing a probable guide for experimental and industrial applications.