Wei Li^1,2, Benjian Zou¹, Yuxiang Luo², Ning Yang², Faye Zhang^1,*, Mingshun Jiang¹, Lei Jia¹

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 485-500, 2023, DOI:10.32604/sdhm.2023.025989 - 17 November 2023

Abstract As a critical structure of aerospace equipment, aluminum alloy stiffened plate will influence the stability of spacecraft in orbit and the normal operation of the system. In this study, a GWO-ELM algorithm-based impact damage identification method is proposed for aluminum alloy stiffened panels to monitor and evaluate the damage condition of such stiffened panels of spacecraft. Firstly, together with numerical simulation, the experimental simulation to obtain the damage acoustic emission signals of aluminum alloy reinforced panels is performed, to establish the damage data. Subsequently, the amplitude-frequency characteristics of impact damage signals are extracted and put… More >

Yanming Wang^1,2,3, Kebin Jia^1,2,3,*, Pengyu Liu^1,2,3

Journal on Internet of Things, Vol.2, No.3, pp. 109-120, 2020, DOI:10.32604/jiot.2020.010138 - 16 September 2020

Abstract With the global climate change, the high-altitude detection is more and more important in the climate prediction, and the input-output characteristic curve of the air pressure sensor is offset due to the interference of the tested object and the environment under test, and the nonlinear error is generated. Aiming at the difficulty of nonlinear correction of pressure sensor and the low accuracy of correction results, depth neural network model was established based on wavelet function, and Levenberg-Marquardt algorithm is used to update network parameters to realize the nonlinear correction of pressure sensor. The experimental results More >

Yanling Bai^1,*, Feng Liu²

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 307-319, 2019, DOI:10.32604/fdmp.2019.07833

Abstract Levenberg-Marquardt (LM) algorithm is applied for the optimization of the heat transfer of a batch reactor. The validity of the approach is verified through comparison with experimental results. It is found that the mathematical model can properly describe the heat transfer relationships characterizing the considered system, with the error being kept within ±2°C. Indeed, the difference between the actual measured values and the model calculated value curve is within ±1.5°C, which is in agreement with the model assumptions and demonstrates the reliability and effectiveness of the algorithm applied to the batch reactor heat transfer model. More >

Shuai Yuan¹, Guizhi Wang^1,*, Jibo Chen¹, Wei Guo²

Journal on Artificial Intelligence, Vol.1, No.2, pp. 69-88, 2019, DOI:10.32604/jai.2019.06535

Abstract This paper develops a joint model utilizing the principal component analysis (PCA) and the back propagation (BP) neural network model optimized by the Levenberg Marquardt (LM) algorithm, and as an application of the joint model to investigate the damages caused by typhoons for a coastal province, Fujian Province, China in 2005-2015 (latest). First, the PCA is applied to analyze comprehensively the relationship between hazard factors, hazard bearing factors and disaster factors. Then five integrated indices, overall disaster level, typhoon intensity, damaged condition of houses, medical rescue and self-rescue capability, are extracted through the PCA; Finally,… More >

Yajie Sun^1,2,*, Yanqing Yuan², Qi Wang², Sai Ji^1,2, Lihua Wang³, Shaoen Wu⁴, Jie Chen², Qin Zhang²

Journal of Quantum Computing, Vol.1, No.1, pp. 1-8, 2019, DOI:10.32604/jqc.2019.05788

Abstract A method is proposed based on the transmissibility function and the Online Sequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to the impact damage of composite materials. First of all, the transmissibility functions of the undamaged signals and the damage signals at different points are calculated. Secondly, the difference between them is taken as the damage index. Finally, principal component analysis (PCA) is used to reduce the noise feature. And then, input to the online sequence limit learning neural network classification to identify damage and confirm the damage location. Taking the amplitude of the More >