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IUKF neural network modeling for FOG temperature drift

Journal of Systems Engineering and Electronics 2013年第5期24卷 838-844页

作者： Feng Zha Jiangning Xu Jingshu Li Hongyang He Department of Navigation Engineering Naval University of Engineering

A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.

关键词： fiber optic gyro (FOG) temperature drift neural net- work iterated unscented Kalman filter (IUKF).

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Two Algorithm Contrast on temperature drift in Metal Tube Rotameter

Two Algorithm Contrast on Temperature Drift in Metal Tube Ro...

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第二届21世纪和谐核电系统国际会议（ISSNP2008）

作者： Ning Jing~1,Peng Jie-gang~2 1.School of Mechanical Eng,Southwest Jiaotong University,Chengdu Sichuan 610031,PR China 2.School of Automation,University of Electronic Science and Technology of China,Chengdu,Sichuan 610054,PR China

A temperature compensation algorithm was researched based on BP neural network in metal tube *** effect of temperature interference on sense organ(hall organ) of Metal Tube Rotameter was *** temperature drift on hall metal tube rotameter was investigated in thermotank by *** fitting and BP neural network was proposed based on *** results of the two methods were *** last,an off-line training method based on virtual instrument has been put forward.

关键词： Hall Element temperature drift Polynomial Fitting BP Neural Network

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Extraction of the key infrared radiation temperature features concerning stress and crack evolution of loaded rocks

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International Journal of Mining Science and Technology 2024年第8期34卷 1059-1081页

作者： Wei Liu Liqiang Ma Michel Jaboyedoff Marc-Henri Derron Qiangqiang Gao Fengchang Bu Hai Sun Key Laboratory of Xinjiang Coal Resources Green Mining(Xinjiang Institute of Engineering) Ministry of EducationUrumqi 830023China Xinjiang Key Laboratory of Coal-bearing Resources Exploration and Exploitation Xinjiang Institute of EngineeringUrumqi 830023China Xinjiang Engineering Research Center of Green Intelligent Coal Mining Xinjiang Institute of EngineeringUrumqi 830023China School of Mines China University of Mining&TechnologyXuzhou 221116China Institute of Earth Sciences University of LausanneLausanne 1015Switzerland School of Civil Engineering Liaoning Petrochemical UniversityFushun 113001China

The infrared radiation temperature(IRT)variation concerning stress and crack evolution of rocks is a critical focus in rock mechanics domain and engineering disaster *** this paper,a methodology to extract the key IRT features related to stress and crack evolution of loaded rocks is ***,the wavelet denoising and reconstruction in thermal image sequence(WDRTIS)method is employed to eliminate temporal noise in thermal image ***,the adaptive partition temperature drift correction(APTDC)method is introduced to alleviate temperature *** this basis,the spatial noise correction method based on threshold segmentation and adaptive median filtering(OTSU-AMF)is proposed to extract the key IRT features associated with microcracks of loaded *** temperature drift correction,IRT provides an estimation of the thermoelastic factor in rocks,typically around 5.29×10^(-5) MPa^(-1) for *** reveal that the high-temperature concentrated region in cumulative thermal images of crack evolution(TICE)can elucidate the spatiotemporal evolution of localized ***,heat dissipation of crack evolution(HDCE)acquired from TICE quantifies the progressive failure process of *** proposed methodology enhances the reliability of IRT monitoring results and provides an innovative approach for conducting research in rock mechanics and monitoring engineering disasters.

关键词： Infrared radiation(IR) temperature drift Spatial background noise Rock fracture Average infrared radiation temperature(AIRT) Heat dissipation of crack evolution(HDCE)

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