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NEW METHOD OF EXTRACTING WEAK FAILURE INFORMATION IN GEARBOX BY COMPLEX WAVELET DENOISING

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Chinese Journal of Mechanical Engineering 2008年第4期21卷 87-91页

作者： CHEN Zhixin xu jinwu YANG Debin School of Mechanical Engineering University of Science and Technology Beijing Beijing 100083 China

Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new signal-denoising method which uses local adaptive algorithm based on dual-tree complex wavelet transform （DT-CWT） is introduced to extract weak failure information in gear, especially to extract impulse components. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking the advantage of near shift-invariance of DT-CWT, the higher signal-to-noise ratio （SNR） than common wavelet denoising methods can be obtained. Experiments of extracting periodic impulses in gearbox vibration signals indicate that the method can extract incipient fault feature and hidden information from heavy noise, and it has an excellent effect on identifying weak feature signals in gearbox vibration signals.

关键词： Dual-tree complex wavelet transform Signal-denoising Gear fault diagnosis Early fault detection

Prediction of mechanical properties for deep drawing steel by deep learning

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International Journal of Minerals,Metallurgy and Materials 2023年第1期30卷 156-165页

作者： Gang xu Jinshan He Zhimin Lü Min Li jinwu xu Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijing 100083China Suzhou Baolian Heavy Industry Co. Suzhou 215131China

At present,iron and steel enterprises mainly use“after spot test ward”to control final product ***,it is impossible to realize on-line quality predetermining for all products by this traditional approach,hence claims and returns often occur,resulting in major eco-nomic losses of *** order to realize the on-line quality predetermining for steel products during manufacturing process,the predic-tion models of mechanical properties based on deep learning have been proposed in this ***,the mechanical properties of deep drawing steels were predicted by using LSTM(long short team memory),GRU(gated recurrent unit)network,and GPR(Gaussian process regression)model,and prediction accuracy and learning efficiency for different models were also ***,on-line re-learning methods for transfer learning models and model parameters were *** experimental results show that not only the prediction accuracy of optimized trans-fer learning models has been improved,but also predetermining time was shortened to meet real time requirements of on-line property *** industrial production data of interstitial-free(IF)steel was used to demonstrate that R2 value of GRU model in training stage reaches more than 0.99,and R2 value in testing stage is more than 0.96.

关键词： machine learning recurrent natural network transfer learning on-line prediction deep drawing steel mechanical properties

HIGHER ORDER SPECTRAL ANALYSIS IN FAULT DIAGNOSIS OF ROTORS

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Chinese Journal of Mechanical Engineering 2001年第1期14卷 40-44页

作者： Yang Jiangtian xu jinwu School of Mechanical Engineering, Beijing University of Sicence and Technology 北京科技大学机械工程学院北京

The nonlinear properties of rotating machinery vibration signals are presented. The relationship between faults and quadratic phase coupling is discussed. The mechanism that gives rise to quadratic phase coupling is analyzed, and the coupling models are summarized. As a result, higher order spectra analysis is introduced into fault diagnosis of rotors. A brief review of the properties of higher order spectra is presented. Furthermore, the bicoherence spectrum is employed to extract the features that signify the machinery condition. Experiments show that bicoherence spectrum patterns of different faults are quite different, so it is proposed to identify the faults in rotors.

关键词： Rotor Fault diagnosis Quadratic phase coupling Higher order spectra Bicoherence spectrum

A New Genetic Algorithm Based on Niche Technique and Local Search Method

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Journal of University of Science and Technology Beijing 2001年第1期8卷 63-68页

作者： jinwu xu, Jiwen Liu Mechanical Engineering School, University of Science and Technology Beijing, Beijing 100083, China Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China

The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. In this paper, a new generic algorithm based on niche technique and local search method is presented under the consideration of inadequacies of the simple genetic algorithm. In order to prove the adaptability and validity of the improved genetic algorithm, optimization problems of multimodal functions with equal peaks, unequal peaks and complicated peak distribution are discussed. The simulation results show that compared to other niching methods, this improved genetic algorithm has obvious potential on many respects, such as convergence speed, solution accuracy, ability of global optimization, etc.

关键词： genetic algorithm (GA) niche technique local search method

Surface Inspection System for Cold Rolled Strips Based on Image ProcessingTechnique

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International Journal of Minerals,Metallurgy and Materials 1999年第4期13卷 296-298页

作者： Ke xu1 jinwu xu2 Shouli Lu1(l Material Science and Engineering School, University of Science and Technology Beijing, Beijing 100083, China2 Mechanical Engineering School, University of Science and Technology Beding, Beliing 100083, China) Material Science and Engineering School University of Science and Technology Beijing Beijing 100083 China Mechanical Engineering School University of Science and Technology Beijing Beijing 100083 China

A new surface inspection system for cold rolled strips based on image processing is introduced. The system is equipped withtwo different illumination structures and CCD matrix cameras. The structure and image processing of the inspection system are described. Some efficient algorithms for image processing and classification are presented. The system is tested with strip samples fromcold rolling plants. The results show that the system can detect and recognize six common defects of cold rolled strips successfully.

关键词： surface inspection system cold rolled strip image processing

Online application of automatic surface quality inspection system to finishing line of cold rolled strips

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Journal of University of Science and Technology Beijing 2003年第4期10卷 38-41页

作者： Hao Sun, Ke xu, and jinwu xuNational Engineering Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing 100083, China National Engineering Research Center of Advanced Rolling. University of Science and Technology Beijing Beijing 100083 China

An automatic surface quality inspection system installed on a finishing lineof cold rolled strips is introduced. The system is able to detect surface defects on cold rolledstrips, such as scratches, coil breaks, rusts, roll imprints, and so on. Multiple CCD area scancameras were equipped to capture images of strip surface simultaneously. Defects were detectedthrough 'Dark-field illumination' which is generated by LED illuminators. Parallel computationtechnique and fast processing algorithms were developed for real-time data processing. Theapplication to the production line shows that the system is able to detect defects effectively.

关键词： surface inspection cold rolled strip finishing line CCD cameras imageprocessing

A machine learning-based crystal graph network and its application in development of functional materials

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Materials Genome Engineering Advances 2024年第3期2卷 107-116页

作者： Gang xu You xue Xiaoxiao Geng Xinmei Hou jinwu xu Collaborative Innovation Center of Steel Technology University of Science and Technology BeijingBeijingChina Institute for Carbon Neutrality University of Science and Technology BeijingBeijingChina

An active area of MGI(Materials Genome Initiative)/MGE(Materials Genome Engineering)is to accelerate the development of new materials by means of active learning and“digital trial-error”using a prediction model of material *** learning methods have widely been employed for predicting crystalline materials properties with crystal graph neural networks(CGNN).The prediction accuracy of the state-of-the-art(SOTA)CGNN models based on big models and big data is generally ***,for the development of some classes of materials,the datasets obtained by experiments are usually lacking due to costly experiments and measurement *** lack of datasets will impact the accuracy of CGNN models and may result in overfitting during training *** paper proposes a simplified crystal graph convolutional neural network(S-CGCNN)which possesses higher prediction accuracy while reducing the vast amount of train datasets and computation *** S-CGCNN model has successfully predicted properties of crystalline materials,such as piezoelectric materials and dielectric materials,and increased the prediction accuracy up to 12%-20%than existing SOTA CGNN ***,the distribution map between properties and compositions of materials has been built to screen the latent space of candidate materials efficiently by principal component analysis.

关键词： crystal graph neural network crystalline materials functional material machine learning

维普期刊数据库评论

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维普期刊数据库

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大学科技创新与人才培养模式改革问题的思考

中国高教研究 2008年第1期 10-12页

作者：徐金梧北京科技大学校长教授北京100088

大学是科技进步和人才培养的结合点。与一些办学历史悠久的世界著名大学相比,我国高校在培养人才的创新意识、创新精神和创新能力上还有很大差距。要把一批中国大学办成世界著名大学,就需要我们找准大学自身的定位,保持和弘扬自己的办... 详细信息

大学是科技进步和人才培养的结合点。与一些办学历史悠久的世界著名大学相比,我国高校在培养人才的创新意识、创新精神和创新能力上还有很大差距。要把一批中国大学办成世界著名大学,就需要我们找准大学自身的定位,保持和弘扬自己的办学特色,积极借鉴国外大学培养创新型人才方面成功的经验,突破现有的办学理念和办学模式,构筑中国特色的创新人才培养体系。同时要大力倡导学术自由、勇于创新、宽容失败的大学文化,在科技创新中培养一大批富有创新意识和创新能力的杰出人才,努力在自主创新和原始创新中有所作为。

关键词：大学科技创新人才培养大学文化

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大型构件动态固有频率和阻尼系数辨识方法

机械工程学报 2001年第6期37卷 72-75,81页

作者：吕志民徐金梧北京科技大学机械工程学院北京100083

大型构件在实际工作环境中的系统动态固有频率和粘性阻尼系数辨识一直是一个“棘手”的问题。提出了基于非线性建模和小波变换方法的大型构件的固有频率和粘性阻尼的分析方法 ,成功地检测出我国某大型水轮机轴系的动态固有频率和粘性阻... 详细信息

大型构件在实际工作环境中的系统动态固有频率和粘性阻尼系数辨识一直是一个“棘手”的问题。提出了基于非线性建模和小波变换方法的大型构件的固有频率和粘性阻尼的分析方法 ,成功地检测出我国某大型水轮机轴系的动态固有频率和粘性阻尼系数。通过仿真结果与理论值的比较 ,证实了该方法的有效性和精确性。

关键词：系统辨识动态固有频率粘性阻尼系大型构件水轮机