Chinese Journal of Mechanical Engineering最新文献

Advanced Pt/PANI-Modified TiO2/PVAc Fiber Electrode for Enhanced Sensitivity in Glucose Detection 新型Pt/ pani修饰TiO2/PVAc纤维电极提高葡萄糖检测灵敏度

2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.cjme.2025.100154

Gang Yu, Qianguo Yu, Zhaobang An, Yixuan Zhu, Kedong Bi

{"title":"Advanced Pt/PANI-Modified TiO2/PVAc Fiber Electrode for Enhanced Sensitivity in Glucose Detection","authors":"Gang Yu, Qianguo Yu, Zhaobang An, Yixuan Zhu, Kedong Bi","doi":"10.1016/j.cjme.2025.100154","DOIUrl":"https://doi.org/10.1016/j.cjme.2025.100154","url":null,"abstract":"The global epidemic of diabetes urgently requires continuous and non-invasive glucose monitoring techniques. This article presents the development of a novel Pt/PANI-modified TiO 2 /PVAc nanofiber electrochemical sensor to address this challenge. In this research, the doping of Pt particles and PANI particles has effectively enhanced the electrochemical performance of the electrode. TiO 2 is first mixed with PVAc powder and then dissolved in an acetone/ethanol solution. Subsequently, fibers are fabricated through electrospinning technology and laid onto the electrode surface. The incorporation of TiO 2 offers more active sites for the deposition of Pt and PANI, thereby strengthening the stability of the overall structure. Furthermore, after the immobilization of Pt and PANI, the designed electrode demonstrates more outstanding performance in glucose detection. Experiments have shown that the peak current of the Pt/PANI/TiO₂/PVAc electrode in the electrochemical detection of glucose is 11 times that of the TiO₂/PVAc electrode. The results indicate that the ultimate electrode exhibits a detection limit of 0.001 mM, with a sensitivity of 7.818 μA·mM⁻¹·cm⁻², and a linear detection range spanning from 50 μM to 7 mM. These characteristics render it suitable for applications involving the detection of physiological glucose concentrations. This work demonstrated a promising step towards practical and effective wearable glucose monitoring, offering a safer and more convenient alternative for diabetes management.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"1 1","pages":"100154-100154"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147899647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Virtual Impedance Adaptation of Lower-Limb Exoskeleton for Human Performance Augmentation Based on Deep Reinforcement Learning 基于深度强化学习的下肢外骨骼虚拟阻抗自适应人体性能增强

2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2025-10-09 DOI: 10.1186/s10033-025-01355-y

Ranran Zheng, Zhiyuan Yu, Hongwei Liu, Junqin Lin, Bo Zeng, Longfei Jia

{"title":"Virtual Impedance Adaptation of Lower-Limb Exoskeleton for Human Performance Augmentation Based on Deep Reinforcement Learning","authors":"Ranran Zheng, Zhiyuan Yu, Hongwei Liu, Junqin Lin, Bo Zeng, Longfei Jia","doi":"10.1186/s10033-025-01355-y","DOIUrl":"https://doi.org/10.1186/s10033-025-01355-y","url":null,"abstract":"Abstract This paper proposes virtual impedance adaptation of the lower-limb exoskeleton for human performance augmentation (LEHPA) based on deep reinforcement learning (VIADRL) to mitigate reliance on model accuracy and address the ever-changing human-exoskeleton interaction (HEI) dynamics. The classical sensitivity amplification control strategy is expanded to the virtual impedance control strategy with more learnable virtual impedance parameters. The adjustment of these virtual impedance parameters is formalized as finding the optimal policy for a Markov Decision Process and can then be effectively resolved using deep reinforcement learning algorithms. To ensure safe and efficient policy training, a multibody simulation environment is established to facilitate the training process, supplemented by the innovative hybrid inverse-forward dynamics simulation approach for executing the simulation. For comparison purposes, the SADRL strategy is introduced as a benchmark. A novel control performance evaluation method based on the HEI forces at the back, thighs, and shanks is proposed to quantitatively evaluate the performance of our proposed VIADRL strategy. The VIADRL controller is systematically compared with the SADRL controller at five selected walking speeds. The lumped ratio of HEI forces under the SADRL strategy relative to those under the SADRL strategy is as low as 0.81 in simulation and approximately 0.89 on the LEHPA prototype. The overall reduction of HEI forces demonstrates the superiority of the VIADRL strategy in comparison to the SADRL strategy.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cjme.springeropen.com/counter/pdf/10.1186/s10033-025-01355-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147914875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Variable-width Legged Robot: Single-DoF Overconstrained Morphing Trunk Mechanism and Morphology-Adaptive Legged Locomotion 变宽腿机器人：单自由度超约束变形主干机构与形态自适应腿运动

2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2025-07-28 DOI: 10.1186/s10033-025-01318-3

Yinghui Li, Hao Chen, Hang Fu, Weizhong Guo

{"title":"Variable-width Legged Robot: Single-DoF Overconstrained Morphing Trunk Mechanism and Morphology-Adaptive Legged Locomotion","authors":"Yinghui Li, Hao Chen, Hang Fu, Weizhong Guo","doi":"10.1186/s10033-025-01318-3","DOIUrl":"https://doi.org/10.1186/s10033-025-01318-3","url":null,"abstract":"Abstract Animals can adapt to their surroundings by modifying their trunk morphology, whereas legged robots currently utilize rigid trunks. This study introduces a single-degree-of-freedom (DoF), six-revolute (6R) morphing trunk mechanism designed to equip legged robots with variable-width capabilities. Subsequently, a morphology-aware locomotion learning pipeline, based on reinforcement learning, is proposed for real-time trunk-width deformation and adaptive legged locomotion. The proposed variable-width trunk is integrated into a quadrupedal robot, and the learning pipeline is employed to train the adaptive locomotion controller of this robot. This study has three key contributions: (1) An overconstrained morphing mechanism is designed to achieve single-DoF trunk-width deformation, thereby minimizing power consumption and simplifying motion control. (2) A novel morphology-adaptive learning pipeline is introduced that utilizes adversarial joint-level motion imitation to ensure coordination consistency during morphological adaptation. This method addresses dynamic disturbances and interlimb coordination disruptions caused by width modifications. (3) A historical proprioception-based asymmetric neural network architecture is utilized to attain implicit terrain perception without visual input. Collectively, these developments enable the proposed variable-width legged robot to maintain consistent locomotion across complex terrains and facilitate rapid width deformation in response to environmental changes. Extensive simulation experiments validate the proposed design and control methodology.","PeriodicalId":10115,"journal":{"name":"Chinese Journal of Mechanical Engineering","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147911701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Motion Planning for Autonomous Driving with Real Traffic Data Validation 利用真实交通数据验证自动驾驶的运动规划

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-10 DOI: 10.1186/s10033-023-00968-5

Wenbo Chu, Kai Yang, Shen Li, Xiaolin Tang

引用次数: 0

Multi-Objective Optimization of VBHF in Deep Drawing Based on the Improved QO-Jaya Algorithm 基于改进 QO-Jaya 算法的深图中 VBHF 的多目标优化

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-05 DOI: 10.1186/s10033-023-00985-4

Xiangyu Jiang, Zhaoxi Hong, Yixiong Feng, Jianrong Tan

引用次数: 0

Nonlinear Impact Damage Evolution of Charpy Type and Analysis of Its Key Influencing Factors 夏比型非线性冲击损伤演变及其主要影响因素分析

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-03 DOI: 10.1186/s10033-023-00986-3

Jianfeng Mao, Qian Xu, Jiadong Yang, Chi Cao, Dasheng Wang, Fengping Zhong, Mingya Chen

引用次数: 0

A Dual-Task Learning Approach for Bearing Anomaly Detection and State Evaluation of Safe Region 安全区域轴承异常检测和状态评估的双任务学习方法

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-03 DOI: 10.1186/s10033-023-00978-3

Yuhua Yin, Zhiliang Liu, Bin Guo, Mingjian Zuo

引用次数: 0

Electrochemical Hydrogen Charging on Corrosion Behavior of Ti-6Al-4V Alloy in Artificial Seawater 电化学充氢对人工海水中 Ti-6Al-4V 合金腐蚀行为的影响

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-02 DOI: 10.1186/s10033-023-00983-6

Yanxin Qiao, Yue Qin, Huiling Zhou, Lanlan Yang, Xiaojing Wang, Zhengbin Wang, Zhenguang Liu, Jiasheng Zou

引用次数: 0

Optimization of Fixture Number in Large Thin-Walled Parts Assembly Based on IPSO 基于 IPSO 的大型薄壁零件装配中夹具数量的优化

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2024-01-02 DOI: 10.1186/s10033-023-00972-9

Changhui Liu, Jing Wang, Ying Zheng, Ke Jin, Jianbo Yu, Jianfeng Liu

引用次数: 0

Research on Energy Efficiency Characteristics of Mining Shovel Hoisting and Slewing System Driven by Hydraulic-Electric Hybrid System 液压-电动混合动力系统驱动矿用铲车提升和回转系统的能效特性研究

IF 4.2 2区工程技术

Chinese Journal of Mechanical Engineering Pub Date : 2023-12-19 DOI: 10.1186/s10033-023-00970-x

Xiangyu Wang, Lei Ge, Yunhua Li, Long Quan

引用次数: 0