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Channel Pruning for Efficient Convolution Neural Networks

Journal of Physics: Conference Series 2019年第2期1302卷

作者： Wei Wang Liqiang Zhu School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing 100044 China Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control Technology (Beijing Jiaotong University) Ministry of Education Beijing 100044 China

In this paper, we propose a novel pruning method using feature maps Ln-norm to compress deep convolutional neural networks (CNNs) with large model size and long inference time. Different from existing pruning methods, which are mainly based on convolution kernels L1-norm, the proposed method uses output feature maps Ln-norm, where n is a variable. This method can accurately identify the redundant convolution filters and has good compression performance. The experiments on ImageNet show that the proposed method outperforms previous methods and is generally suitable for any CNNs models.

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Design and experiment of test system for simulating aero-engine burn fragments fault 2

Design and experiment of test system for simulating aero-eng...

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2nd International Conference on Frontiers of Sensors Technologies, ICFST 2017

作者： Manguo, Huang Wei, Liu Defeng, Liu Yanshan, Wang Xin, Li Advanced Sensor Technology Center AVIC Beijing Changcheng Aeronautic Measurement and Control Technology Research Institute Beijing China Aviation Key Laboratory of Science and Technology On Special Condition Monitoring Sensor Technology Beijing China

ISBN: (纸本)9781509048601

The aero-engine gas path fault is the important aero-engine fault and has high frequency. This fault must be found timely and solved as early as possible to make sure the normal work of aero-engine and the safe flight of the airplane. The burn fragments fault is a common fault aero-engine gas path fault. The special aero-engine gas path fault simulation test system is necessary if we want to study the burn fragments fault efficiently and deeply. Based on the electrostatic monitoring technology, a kind of test system of aero-engine gas path fault was designed in this paper, and the burn fragments fault was simulated by the test system. Finally, the experiments for aero-engine gas path faults simulations were performed, and the effectiveness of simulation test system of aero-engine gas path fault was verified. © 2017 IEEE.

关键词： Electrostatics

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Structural Synthesis of 2T3R Hybrid Kinematic Mechanism Based on G_F Set

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Journal of Donghua University(English Edition) 2017年第3期34卷 405-414页

作者：曹毅秦友蕾王见刘俊辰王琨 School of Mechanical Engineering Jiangnan University Wuxi 214122 China Key Laboratory of System Control and Information Processing Shanghai 200240 China State Key Laboratory of Mechanical System and Vibration Shanghai 200240 China Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Wuxi 214122 China

The structural synthesis of mechanisms is a prerequisite of mechanical design. Thereby, it is necessary to address special attention to the structural synthesis of mechanisms,especially for the structural synthesis of hybrid kinematic mechanisms( HKMs). This paper presents a very simple yet very effective method of structural synthesis for HKM based on the set theory. The basic concept and mathematical operation of Generalized Function Set( G_F set) are firstly introduced. Based on G_F set,a type synthesis principle for serial mechanisms,parallel mechanisms and HKMs is presented,respectively. Especially,a detailed algorithm of type synthesis for HKM is proposed as well. It is shown that type synthesis of HKM can be developed by the combination of elements of G_F setand rotation axis transfer theorem. In order to demonstrate the applicability of the type synthesis principle presented in the paper,structure synthesis of 2T3 R HKMs are accomplished,where T and R denote translational and rotational degree-of-freedom( DoF),respectively. And further research shows that the structures of 2T3 R HKMs can be categorized into two types,i. e.,G(_F~Ⅰ) and G(_F~Ⅱ).

关键词： kinematic rotation translational serial freedom effector prerequisite robot intersection unified

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Parametric Study of MRR and Surface Integrity for 304 Stainless Steel in EDM

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IOP Conference Series: Materials Science and Engineering 2019年第1期493卷

作者： Chengchang Niu Chenxue Wang Zhang Qiang Dehuai Zeng Lin Cheng College of Mechatronics and Control Engineering Shenzhen University Guangdong 518060 PR China Shenzhen Key Laboratory of Advanced Manufacturing Technology for Mold &Die Shenzhen University Shenzhen 518060 Guangdong PR China

304 stainless steel is a promising material that is extensively used in manufacturing industries. Herein, the influence of the machining parameters electrical discharge machining (EDM) on the material removal rate (MRR) and surface integrity of 304 stainless steel are investigated. The improvement in the MRR with the optimum experimental conditions compared to the initial condition is 64% by the Taguchi methodology. The topography of the section surface produced by EDM with different pulse durations is studied. We founded that the section surface integrity becomes poorer with the increase in the pulse duration.

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Research on Compound Faults Diagnosis of Rolling Bearings Based on Parallel Dual Q-Factors and AMCKD

Research on Compound Faults Diagnosis of Rolling Bearings Ba...

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International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Lingli Cui Jianxi Du Huaqing Wang Jianguo Wang Beijing University of Technology Key Laboratory of Advanced Manufacturing Technology Beijing China Beijing University of Technology Beijing Engineering Research Center of Precision Measurement Technology and Instruments China Beijing University of Chemical Technology School of Mechanical & Electrical Engineering Chaoyang District Beijing China Inner Mongolia University of Science&Technology School of mechanical engineering China

ISBN: (纸本)9781538660584;9781538660577

The rolling bearings often suffer from compound faults in practice, moreover, several faults add together and interfere with each other, which make it difficult to separate week fault signals from them through conventional ways. In order to improve the compound faults diagnosis of rolling bearings via signals' separation, the paper proposes a new method to identify compound faults from mixed-signals, which is based on parallel dual Q-factors method and the adaptive maximum correlation kurtosis deconvolution (AMCKD) method. With the approach, the vibration signal is firstly decomposed into high and low resonance components by the sparse decomposition based on dual Q-factors method, which can sparsely represent the signal and extract the fault impact signal. Then, the low-resonance component is processed by AMCKD, and the AMCKD can adaptively optimize the selection of parameters M and L. Finally, the compound faults can be separated effectively by the method, which makes the fault features more easily extracted and more clearly identified. Simulated analysis result validates the effectiveness of the proposed method in compound faults separating.

关键词： Compounds Q-factor Feature extraction Finite impulse response filters Fault diagnosis Rolling bearings Vibrations

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Design of temperature compensation for silicon-sapphire pressure sensor

Design of temperature compensation for silicon-sapphire pres...

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2017 IEEE International Conference on Imaging Systems and Techniques, IST 2017

作者： Manguo, Huang Defeng, Liu Chao, Lu Zhanshe, Guo Xin, Li Advanced Sensor Technology Center AVIC Beijing Changcheng Aeronautic Measurement Control Technology Research Institute Aviation Key Laboratory of Science and Technology Special Condition Monitoring Sensor Technology Beijing China School of Instrument Science and Opto-electronics Engineering State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9781538616208

In order to solve the problem that the temperature drift of the silicon-on-sapphire pressure sensor is too large to reduce the accuracy of pressure measurement at high temperature, a temperature compensation scheme based on a single chip is proposed. The temperature of the working environment is obtained by a PT100, and integrated with the output of pressure sensor to calculate the compensated pressure sensor. Problems of power supply and signal acquisition are solved by the high precision, low drift voltage and current references, programmable amplifiers and high precision ADCs on chip. According to the working characteristics of the silicon-on-sapphire pressure sensor, an efficient temperature compensation algorithm is designed, and written to the on-chip ARM processor. The experimental results show that the maximum measurement error of pressure in the temperature range of -20∼250°C and measurement range of 0∼28 MPa is 8.37%FS before compensation and reduced to 0.3%FS after compensation. The accuracy of the sensor is greatly improved by the compensation system. © 2017 IEEE.

关键词： Pressure sensors

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Effects of belt’s adhesive wear on surface integrity in dry belt finishing

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Procedia CIRP 2018年 71卷 31-34页

作者： Wenxi Wang Ferdinando Salvatore Joël Rech Jianyong Li School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing 100044 China Université de Lyon CNRS École nationale d’ingénieurs de Saint-Étienne LTDS UMR5513 42023 Saint-Étienne cedex 2 France Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control Technology Ministry of Education Beijing 100044 China

Adhesive wear on abrasive belt, as an abnormal abrasion mode, often occurs due to improper working conditions in dry belt finishing, which will accordingly modify basic action mechanisms. In order to study its effects on surface integrity, a pair of experiments with and without adhesive wear is carried out by controlling finishing duration. The results reveal that adhesive wear has revealed a potential to further decrease surface roughness and enhance bearing ability compared to the common finishing process. This function is positively correlated with the occurrence frequency of the adhesive wear. Meanwhile, the cutting ability of abrasive belt has been significantly reduced since adhesive wear happened because the cutting action of grains was mainly replaced by sliding and plowing. Besides, significant compressive residual stresses are generated indistinguishable under a dry condition no matter with or without adhesive wear.

关键词： Dry belt finishing adhesive wear surface integrity

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MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv

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arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

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Input optics systems of the KAGRA detector during O3GK (vol 2023, 023F01, 2023)

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PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS 2023年第5期2023卷

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M. A. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chiang, C-I Chu, H. Chu, Y-K Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fujikawa, Y. Fukunaga, M. Fukushima, M. Furuhata, T. Gao, D. Ge, G-G Ha, S. Hagiwara, A. Haino, S. Han, W-B Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B-H Huang, G-Z Huang, H-Y Huang, P. Huang, Y-C Huang, Y-J Hui, D. C. Y. Ide, S. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Ito, K. Itoh, Y. Izumi, K. Jeon, C. Jin, H-B Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kang, G. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J. Kim, J. C. Kim, Ws Kim, Y-M Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A. K. H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H-S Kuromiya, Y. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H. K. Lee, H. W. Lee, R. Leonardi, M. Li, K. L. Lin, L. C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H. L. Liu, G. C. Luo, L-W Majorana, E. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Nakayama, Y. Narikawa, T. Naticchioni, L. Negishi, R. Quynh, L. Nguyen Ni, W-T Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J. J. Oh, S. H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohta, H. Okutani, Y. Okutomi, K. Oohara, K. Ooi, C. Oshino, S. Otabe, S. Pan, K-C Pang, H. Parisi, A. Park, J. Arellano, F. E. Pena Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shao, L. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E. J. Sotani, H. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Hirosaki Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Republic of Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Road Danshui Dist. New Taipei City 25137 Taiwan Department of Physics

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.

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Ductal carcinoma in situ detection in breast thermography by extreme learning machine and combination of statistical measure and fractal dimension

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Journal of Ambient Intelligence and Humanized Computing 2017年 1-11页

作者： Wang, Shui-Hua Muhammad, Khan Phillips, Preetha Dong, Zhengchao Zhang, Yu-Dong Jiangsu Key Laboratory of Advanced Manufacturing Technology HuaiyinJiangsu223003 China School of Computer Science and Technology Henan Polytechnic University JiaozuoHenan454000 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing China College of Software Convergence Sejong University Seoul Korea Republic of Department of Informatics University of Leicester LeicesterLE1 7RH United Kingdom West Virginia School of Osteopathic Medicine 400 N Lee St LewisburgWV24901 United States Translational Imaging Division and MRI Unit Columbia University and New York State Psychiatric Institute New YorkNY10032 United States

Ductal carcinoma in situ (DCIS) is a severe breast disease. It generates little symptom and may be neglected in prodromal stage. In this study, we developed a novel DCIS detection method based on breast thermography, which can provide earlier alert than other exams. We created a 40 breast-thermogram dataset. We used six statistical measures, and we used fractal dimension to describe the texture measure. The extreme learning machine was used as the classifier. Our developed system yielded a sensitivity of 93.0 ± 2.6%, a specificity of 92.5 ± 2.6%, and an accuracy of 92.8 ± 1.8%. The extreme learning machine was better than support vector machine, artificial neural network, decision tree, and weighted k-nearest neighbors. Besides, our developed system was superior to six state-of-the-art approaches. © 2017 Springer-Verlag GmbH Germany, part of Springer Nature

关键词： Fractal dimension

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