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基于改进滑模控制的水稻直播机路径跟踪研究

农机化研究 2025年第4期47卷 28-34页

作者：徐长赓李彦明刘子翔刘成良上海交通大学机械与动力工程学院上海200240 农业农村部长三角智慧农业技术重点实验室上海200240

为了提高水稻直播机自动作业时路径跟踪的精度和稳定性,提出了一种基于新型非线性滑模面和改进快速变幂次趋近率的滑模路径跟踪控制方法。首先,建立Frenet坐标系下直播机的路径跟踪运动学模型;然后,为保证路径跟踪过程中横向偏差和航向... 详细信息

为了提高水稻直播机自动作业时路径跟踪的精度和稳定性,提出了一种基于新型非线性滑模面和改进快速变幂次趋近率的滑模路径跟踪控制方法。首先,建立Frenet坐标系下直播机的路径跟踪运动学模型;然后,为保证路径跟踪过程中横向偏差和航向偏差全局收敛,采用双曲正切函数设计滑模面;最后,在快速幂次趋近率的基础上设计了变指数幂次项,提高了系统趋近速度并有效抑制了抖振。在Simulink上搭建模型并进行仿真,与基于快速幂次趋近率和指数趋近率的滑模控制方法相比,本文改进滑模控制方法的路径跟踪误差收敛时间最短并且无抖振现象发生。直播机采用改进算法以0.8 m/s的速度在水田实际自动作业时,横向偏差和航向偏差的平均绝对误差为0.016 9 m和1.099 9°,均方差为0.021 5 m和1.499 2°,提高了路径跟踪的精度和稳定性,满足了实际作业需求。

关键词：水稻直播机路径跟踪滑模控制趋近率

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EFFECTS OF POLYTROPIC EXPONENT ON DATA PROCESSING METHODS USED IN CONSTANT VOLUME DISCHARGE

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Chinese Journal of Mechanical Engineering 2008年第1期21卷 53-56页

作者： YANG Lihong liu chengliang ZHA Xuanfang School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai 200093 China School of Mechanical EngTneering Shanghai Jiaotong University Shanghai 200240 China University of Maryland MD 20742 USA

In order to obtain the accurate sonic conductance of solenoid valves, the polytropic exponent is used in the data processing of the discharge method for measuring the flow rate characteristics of pneumatic components. Three data processing principles are first introduced, and then the discharge pressure data obtained from the measured solenoid valve are processed to obtain the sonic conductance with three methods： the partial polytropic exponent method, the complete polytropic exponent method and the adiabatic method. By comparison of the obtained results it indicates that the complete polytropic exponent method is the most accurate. However, the partial polytropic exponent method is of a high applicable value, because it is easy and simple to measure and the obtained results are relatively accurate.

关键词： Polytropic exponent Discharge method Sonic conductance

Tribo-informatics:Concept,architecture,and case study

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Friction 2021年第3期9卷 642-655页

作者： Zhinan ZHANG Nian YIN Shi CHEN chengliang liu Stake Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Friction plays a vital role in energy dissipation,device failure,and even energy supply in modern *** years of research,data and information on tribology research are becoming increasingly *** of the strong systematic and multi-disciplinary coupling characteristics of tribology,tribology information is scattered in various disciplines with different patterns,e.g.,technical documents,databases,and papers,thereby increasing the information entropy of the system,which is inconducive to the preservation and circulation of research *** the development of computer and information science and technology,many subjects have begun to be combined with information technology,and multi-disciplinary informatics has been *** paper describes the combination of information technology with tribology research,presenting the connotation and architecture of tribo-informatics,and providing a case study on implementing the proposed concept and *** proposal and development of tribo-informatics described herein will improve the research efficiency and optimize the research process of tribology,which is of considerable significance to the development of this field.

关键词： tribo-informatics database tribology information technology

Augmentation-based discriminative meta-learning for cross-machine few-shot fault diagnosis

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Science China(Technological Sciences) 2023年第6期66卷 1698-1716页

作者： XIA PengCheng HUANG YiXiang WANG YuXiang liu chengliang liu Jie State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Lab of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Mechanical and Aerospace Engineering Carleton UniversityOttawa ON K1S 5B6Canada

Deep learning methods have demonstrated promising performance in fault diagnosis *** the scarcity of data in industrial scenarios limits the practical application of such methods,transfer learning effectively tackles this issue through crossmachine knowledge ***,the cross-machine few-shot problem,which is a more general industrial scenario,has been rarely *** studies have not considered the cross-machine domain shift problem,which results in poor testing *** paper proposes an augmentation-based discriminative meta-learning method to address this *** the meta-training process,signal transformation is proposed to increase the meta-task diversity for more robust feature learning,and multi-scale learning is combined for more adaptive feature *** the meta-testing process,limited labeled fault information is used to promote model generalization in the target domain through quasi-meta-training based on data ***,a novel hyperbolic prototypical loss is proposed for more discriminative feature representation and separable category prototypes by designing a hyperbolic decision ***-machine few-shot diagnosis experiments were conducted using three datasets from different machines,namely,the bearing,motor,and gear *** effectiveness of the proposed method was verified through ablation and comparison studies.

关键词： fault diagnosis few-shot learning meta-learning data augmentation cross-machine discriminative loss

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Velocity-Incorporated Wear Model of Rolling Guide Shoe Material Selection

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Chinese Journal of Mechanical Engineering 2024年第3期37卷 118-135页

作者： Longye Chen Lingyu Yan chengliang liu Zhinan Zhang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China

To ensure an accurate selection of rolling guide shoe materials,an analysis of the intricate relationship between linear speed and wear is *** element simulations and experimental measurements are employed to evaluate four distinct types of materials:polyurethane,rubber,polytetrafluoroethylene(PTFE),and *** speed-index of each material is measured,serving as a preparation for subsequent ***,the velocity-wear factor is determined,providing insights into the resilience and durability of the material across varying ***,a wear model tailored specifically for viscoelastic bodies is explored,which is pivotal in understanding the wear mechanisms within the *** this model,wear predictions are made under higher speed conditions,facilitating the choice of material for rolling guide *** validate the accuracy of the model,the predicted degree of wear is compared with experimental data,ensuring its alignment with both theoretical principles and real-world *** comprehensive analysis has verified the effectiveness of the model in the selection of materials under high-speed conditions,thereby offering confidence in its reliability and ensuring optimal performance.

关键词： Archard model Wear model Speed-index Wear prediction

Nonlinear Static and Dynamic Stiffness Characteristics of Support Hydraulic System of TBM

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Chinese Journal of Mechanical Engineering 2019年第6期32卷 26-34页

作者： Jianfeng Tao Junbo Lei chengliang liu Wei Yuan School of mechanical engineering Shanghai Jiaotong UniversityShanghai 200240China School of Electronic Information Jiangsu University of Science and TechnologyZhenjiang 212003China

Full-face hard rock tunnel boring machines(TBM)are essential equipment in highway and railway tunnel engineering *** the tunneling process,TBM have serious vibrations,which can damage some of its key *** support system,an important part of TBM,is one path through which vibrational energy from the cutter head is *** reduce the vibration of support systems of TBM during the excavation process,based on the structural features of the support hydraulic system,a nonlinear dynamical model of support hydraulic systems of TBM is *** influences of the component structure parameters and operating conditions parameters on the stiffness characteristics of the support hydraulic system are *** analysis results indicate that the static stiffness of the support hydraulic system consists of an increase stage,stable stage and decrease *** static stiffness value increases with an increase in the *** pre-compression length of the spring in the relief valve a ects the range of the stable stage of the static stiffness,and it does not a ect the static stiffness *** dynamic stiffness of the support hydraulic system consists of a U-shape and reverse *** bottom value of the U-shape increases with the amplitude and frequency of the external force acting on the cylinder body,however,the top value of the reverse U-shape remains *** study instructs how to design the support hydraulic system of TBM.

关键词： Tunnel boring machine Support hydraulic system Nonlinear model Static stiffness characteristics Dynamic stiffness characteristics

Transnational technology transfer network in China:Spatial dynamics and its determinants

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Journal of Geographical Sciences 2022年第12期32卷 2383-2414页

作者： liu chengliang YAN Shanshan Institute for Global Innovation&Development East China Normal UniversityShanghai 200062China Center for World Geography and Geo-strategic Studies East China Normal UniversityShanghai 200062China School of Urban&Regional Science East China Normal UniversityShanghai 200241China

Patent transfer has been regarded as an important channel for the nations and regions to acquire external technology,and also a direct research object to depict the relationship between supply and demand of technology ***,based on traceable patent transfer data,this article has established a dual-pipeline theoretical framework of transnational-domestic technology transfer from the interaction of the global and local(glocal)perspective,and combines social networks,GIS spatial analysis as well as spatial econometric model to discover the spatial evolution of China’s transnational technology channels and its determinant *** is found that:(1)The spatial heterogeneity of the overall network is significant while gradually weakened over time.(2)The eastward shift of the core cities involved in transnational technology channels is accelerating,from the hubs in North America(New York Bay Area,Silicon Valley,Caribbean offshore financial center,etc.)and West Europe(London offshore financial center etc.)to East Asia(Tokyo and Seoul)and Southeast Asia(Singapore),which illustrates China has decreased reliance on the technology from the USA and West Europe.(3)The four major innovation clusters:Beijing-Tianjin-Hebei region(Beijing as the hub),Yangtze River Delta(Shanghai as the hub),The Greater Bay Area(Shenzhen and Hong Kong as the hubs)and north Taiwan(Taipei and Hsinchu as the hubs),are regarded as global technology innovation hubs and China’s distribution centers in transnational technology *** those,Chinese Hong Kong’s betweenness role of technology is strengthened due to linkage of transnational corporations and their branches,and low tax coverage of offshore finance,thus becoming the top city for technology ***,Chinese Taiwan’s core position is diminishing.(4)The breadth,intensity,and closeness of domestic technology transfer are conducive to the expansion of transnational technology import ***,local economic level ha

关键词： patent rights transaction technology transfer’s dual pipelines technology transfer network spatial evolution determinant factor

A novel interpretable multilevel wavelet decomposition deep network for actual heartbeat classification

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Science China(Technological Sciences) 2024年第6期67卷 1842-1854页

作者： JIN YanRui LI ZhiYuan TIAN YuanYuan WEI XiaoYang liu chengliang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240China

Arrhythmias may lead to sudden cardiac death if not detected and treated in time.A supraventricular premature beat(SPB)and premature ventricular contraction(PVC)are important categories of arrhythmia ***,deep learning methods have been applied to the PVC/SPB heartbeats ***,most researchers have focused on time-domain information of the electrocardiogram and there has been a lack of exploration of the interpretability of the *** this study,we design an interpretable and accurate PVC/SPB recognition algorithm,called the interpretable multilevel wavelet decomposition deep network(IMWDDN).Wavelet decomposition is introduced into the deep network and the squeeze and excitation(SE)-Residual block is designed for extracting time-domain and frequency-domain ***,inspired by the idea of residual learning,we construct a novel loss function for the constant updating of the multilevel wavelet decomposition ***,the IMWDDN is evaluated on the Third China Physiological Signal Challenge Dataset and the MIT-BIH Arrhythmia *** comparison results show IMWDDN has better detection performance with 98.51%accuracy and a 93.75%F1-macro on average,and its areas of concern are similar to those of an expert diagnosis to a certain ***,the IMWDDN has good application value in the clinical screening of PVC/SPB heartbeats.

关键词： actual heartbeat classification electrocardiogram interpretable deep network multilevel discrete wavelet decomposition layer SE-Residual block

A multi-scale convolutional neural network for bearing compound fault diagnosis under various noise conditions

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Science China(Technological Sciences) 2022年第11期65卷 2551-2563页

作者： JIN YanRui QIN ChengJin ZHANG ZhiNan TAO JianFeng liu chengliang School of Mechanical Engineering Shanghai Jiao TongUniversityShanghai 200240China

Recently,with the urgent demand for data-driven approaches in practical industrial scenarios,the deep learning diagnosis model in noise environments has attracted increasing ***,the existing research has two limitations:(1)the complex and changeable environmental noise,which cannot ensure the high-performance diagnosis of the model in different noise domains and(2)the possibility of multiple faults occurring simultaneously,which brings challenges to the model *** paper presents a novel anti-noise multi-scale convolutional neural network(AM-CNN)for solving the issue of compound fault diagnosis under different intensity ***,we propose a residual pre-processing block according to the principle of noise superposition to process the input information and present the residual loss to construct a new loss ***,considering the strong coupling of input information,we design a multi-scale convolution block to realize multi-scale feature extraction for enhancing the proposed model’s robustness and ***,a multi-label classifier is utilized to simultaneously distinguish multiple bearing *** proposed AM-CNN is verified under our collected compound fault *** average,AM-CNN improves 39.93%accuracy and 25.84%F1-macro under the no-noise working condition and 45.67%accuracy and 27.72%F1-macro under different intensity noise working conditions compared with the existing ***,the experimental results show that AM-CNN can achieve good cross-domain performance with 100%accuracy and 100%***,AM-CNN has the potential to be an accurate and stable fault diagnosis tool.

关键词： anti-noise residual pre-processing block bearing compound fault multi-label classifier multi-scale convolution feature extraction

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