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Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels

Journal of Computational Information Systems 2014年第1期10卷 9-19页

作者： Wang, Xiao Wang, Hongwei Qi, Chao Sivakumar, Appa Iyer State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Safety Engineering Shenyang Aerospace University Shenyang 110136 China Division of Systems and Engineering Management School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore

This paper proposes a predictive maintenance methodology for a machine in manufacturing with deteriorating quality states represented by multiple deteriorating yield levels. Imperfect minor maintenance and perfect major repair are considered. The underlying yield level cannot be directly obtained. Instead, product quality inspection information is used as the observed system state. The optimal maintenance policy associated with each possible observed system state is learnt by modeling the problem as hidden semi-Markov decision processes and solving it using policy iteration based Q-P learning. Then the future maintenance time can be estimated by re-simulating the system model using the learned maintenance policy. A set of experimental studies is conducted to testify the effectiveness of the proposed methodology and to investigate the impacts of involved system parameters. Copyright © 2014 Binary Information Press.

关键词： Markov processes

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A nonlinear sliding mode observer for the estimation of temperature distribution in the planar solid oxide fuel cell stack

A nonlinear sliding mode observer for the estimation of temp...

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第五届世界氢能技术大会(WHTC2013)

作者： Huan Cheng Xi Li Jianhua Jiang Lin Zhang Jian Li Jie Yang Department of control science and Engineering Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die and Mould Technology Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical and Electronic Information China University of Geosciences Wuhan 430074 China

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An application of circumscribed circle filter in the multi-stencils fast marching method 12

An application of circumscribed circle filter in the multi-s...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Liu, Hong Hung, Chih-Cheng Hu, Huaifei Yu, Mali Song, Enmin School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei 430074 China School of Computing and Software Engineering Southern Polytechnic State University Marietta GA 30060 United States

ISBN: (纸本)9781450308571

We develop an effective method for improving the segmentation result based on the Multi-Stencils Fast Marching method (MSFM). In MSFM, the gradient information of the image plays a vital role for calculating edges. It is straightforward to obtain the edge of good quality images;however, MSFM may not have robust edge maps available for images with spurious edges. Thus, a special multi-direction circumscribed circle filter is proposed to calculate the image gradient information which is then used in the MSFM. Using the new gradient information, better image contours can be obtained with MSFM. The size of the radius used in our circle filter is constant even the standard deviation of zero-mean Gaussian noise changes while the parameters of mean filter and Canny filter for gradient computation have to be correctly selected according to different noisy images. Our proposed method shows that it is effective through the experiments of image segmentation. © 2012 ACM.

关键词： image segmentation

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A novel segmentation method for convex lesions based on dynamic programming with local intra-class variance 12

A novel segmentation method for convex lesions based on dyna...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Yu, Mali Huang, Qiliang Jin, Renchao Song, Enmin Liu, Hong Hung, Chih-Cheng School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei China Radiology Department Second People's Hospital of Nanning Nanning China School of Computing and Software Engineering Southern Polytechnic State University GA United States

ISBN: (纸本)9781450308571

Lesion segmentation plays an important role in medical image processing and analysis. There exist several successful dynamic programming (DP) based segmentation methods for general images. In those methods, the gradient is used as an important factor in the cost function to attract the contours to the boundaries. Since medical images have their characteristics such as low contrast, blurred edges and high noises, the gradient operator cannot work well enough to achieve a satisfactory performance for boundary detection. We define the local intra-class variance and combine it with the dynamic programming method to replace the traditional gradient operation. Experiments on synthetic and X-ray images are carried out and the results are compared with Canny and fast multilevel fuzzy edge detection (FMFED) algorithms. It is demonstrated that the proposed method performs better on medical images with low contrast, blurred edges and high noises. In addition, 483 regions of interest of mammograms randomly extracted from DDSM of the University of South Florida are used to compare our proposed method with the plane-fitting and dynamic programming method (PFDP), and the normalized cut segmentation method (Ncut). The results demonstrate that our method is more accurate and robust than PFDP and Ncut. © 2012 ACM.

关键词： Dynamic programming

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A programmable multi-channel stimulator for array electrodes in transcutaneous electrical stimulation

A programmable multi-channel stimulator for array electrodes...

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IEEE/Institute of Complex Medical Engineering International Conference on Complex Medical Engineering

作者： Xu, Qi Huang, Tao He, Jiping Wang, Yizhao Zhou, Houlun Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Harrington Department of Bioengineering Arizona State University Tempe AZ United States Tongji Medical College Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424493241

Transcutaneous electrical stimulation (TES) has been applied to restore or maintain the muscle activity of paralyzed patients who suffer from spinal cord injuries and related neural impairments for several decades. In this paper, a portable and low-cost versatile stimulator for multichannel TES applications is described. The microcontroller-based programmable stimulator with four bipolar output channels send arbitrarily specified electrical pulses to the element in the electrode array for enabling the complex schemes of muscles. The amplitude and phase of each pulse in the stimulus sequence are independently variable, and the four channels are independently programmable, allowing a wide variety of stimulus patterns. We also designed an output circuit that can provide bi-phasic, voltage-regulated, charge-balanced outputs while avoiding the electrochemical erosion of electrode due to charge accumulation. The proposed stimulator has provided an opportunity for further study of a potential novel electrical stimulator with closed-loop stimulation paradigm suitable for a variety of FES applications, both for experimental and clinical studies. © 2011 IEEE.

关键词： Functional electric stimulation

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A programmable multi-channel stimulator for array electrodes in transcutaneous electrical stimulation

A programmable multi-channel stimulator for array electrodes...

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IEEE/ICME International Conference on Complex Medical Engineering, CME

作者： Qi Xu Tao Huang Jiping He Yizhao Wang Houlun Zhou Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Department of Control Science & Engineering Huazhong University of Science and Technology Wuhan China Harrington Department of Bioengineering Arizona State University Tempe AZ USA Tongji medical College Huazhong University of Science and Technology Wuhan China

关键词： Stimulated emission Algorithms Schottky diodes Biomedical optical imaging

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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International Conference on Mechatronics and Automation

作者： Wang, Yuanyu Li, Yuanzong Zhang, Tianxu Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan CO 030024 China College of Mechanical Engineering TaiYuan University of Technology TaiYuan CO 030024 China Institute for Pattern Recognition and A.I. State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology WuHan CO 430074 China

ISBN: (纸本)9781424451418

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments. © 2010 IEEE.

关键词： Dust

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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Analysis of second order motion

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2009年第3期22卷 344-348页

作者： Sun, Bin Sang, Nong Li, Zheng Zheng, Qing-Qing State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

The study of the second order motion in biological vision is a new source of inspiration for algorithms and research directions in computer vision. In this paper, the second order motion can be divided into three typical group according to the modulation types: spatial modulate motion, temporal modulate motion and spatio-temporal modulate motion. Experiments are conducted on the first order motion perception based on correlation model and the second order motion perception by correlation model preceded with a nonlinear process called texture grabber. The computational results are consistent with the previous suggestion that the second order motions are processed by nonlinear system.

关键词： Modulation

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