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Authors = Minglu Zhu

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20 pages, 3013 KiB  
Article
Data-Driven Prediction of Grape Leaf Chlorophyll Content Using Hyperspectral Imaging and Convolutional Neural Networks
by Minglu Zeng, Xinghui Zhu, Ling Wan, Jian Xu and Luming Shen
Appl. Sci. 2025, 15(10), 5696; https://doi.org/10.3390/app15105696 - 20 May 2025
Viewed by 462
Abstract
Grapes, highly nutritious and flavorful fruits, require adequate chlorophyll to ensure normal growth and development. Consequently, the rapid, accurate, and efficient detection of chlorophyll content is essential. This study develops a data-driven integrated framework that combines hyperspectral imaging (HSI) and convolutional neural networks [...] Read more.
Grapes, highly nutritious and flavorful fruits, require adequate chlorophyll to ensure normal growth and development. Consequently, the rapid, accurate, and efficient detection of chlorophyll content is essential. This study develops a data-driven integrated framework that combines hyperspectral imaging (HSI) and convolutional neural networks (CNNs) to predict the chlorophyll content in grape leaves, employing hyperspectral images and chlorophyll a + b content data. Initially, the VGG16-U-Net model was employed to segment the hyperspectral images of grape leaves for leaf area extraction. Subsequently, the study discussed 15 different spectral preprocessing methods, selecting fast Fourier transform (FFT) as the optimal approach. Twelve one-dimensional CNN models were subsequently developed. Experimental results revealed that the VGG16-U-Net-FFT-CNN1-1 framework developed in this study exhibited outstanding performance, achieving an R2 of 0.925 and an RMSE of 2.172, surpassing those of traditional regression models. The t-test and F-test results further confirm the statistical robustness of the VGG16-U-Net-FFT-CNN1-1 framework. This provides a basis for estimating chlorophyll content in grape leaves using HSI technology. Full article
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9 pages, 2950 KiB  
Proceeding Paper
Cost-Effective Triboelectric-Assisted Sensory Actuator Designed for Intelligent Robot and Exoskeleton
by Haowen Liu, Yusong Chu, Yudong Zhao, Guanyu Zhu, Xuan Li, Minglu Zhu and Tao Chen
Eng. Proc. 2024, 78(1), 11; https://doi.org/10.3390/engproc2024078011 - 18 Apr 2025
Viewed by 2467
Abstract
Joint actuators are the key components in the innovation and iterative optimization of the robots, with a significant impact on both the performances of robots and manufacturing costs. Conventional industrial collaborative robots often use high-precision position and torque sensors, which are not cost-effective [...] Read more.
Joint actuators are the key components in the innovation and iterative optimization of the robots, with a significant impact on both the performances of robots and manufacturing costs. Conventional industrial collaborative robots often use high-precision position and torque sensors, which are not cost-effective or energy-efficient in specific applications like assistive exoskeletons, legged robots, or wheeled robots. Alternatively, we propose a triboelectric-assisted sensory actuator that balances lightweight design, performance, and affordability for large-scale applications. The actuator is composed of a high-power density motor, a low reduction gearbox, and integrated with a rotational triboelectric sensor, which leads to high dynamic performances and low power consumption. The feasibility of the prototype is initially verified by characterizing the angular positioning accuracy and the back drivability. Experiments indicate that the rotational triboelectric sensor is able to accurately detect the angular displacement of the actuator with the self-generated signals. Overall, a highly integrated actuator module with the actuation and sensing circuit is fabricated as a compact design ready for assembling a complete intelligent robot. This actuator holds great potential as a cost-effective, energy-efficient, and versatile solution for modern robotics, crucial for advancing this field and improving human convenience. Full article
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15 pages, 3407 KiB  
Article
Minimalist Design for Multi-Dimensional Pressure-Sensing and Feedback Glove with Variable Perception Communication
by Hao Ling, Jie Li, Chuanxin Guo, Yuntian Wang, Tao Chen and Minglu Zhu
Actuators 2024, 13(11), 454; https://doi.org/10.3390/act13110454 - 13 Nov 2024
Cited by 2 | Viewed by 1219
Abstract
Immersive human–machine interaction relies on comprehensive sensing and feedback systems, which enable transmission of multiple pieces of information. However, the integration of increasing numbers of feedback actuators and sensors causes a severe issue in terms of system complexity. In this work, we propose [...] Read more.
Immersive human–machine interaction relies on comprehensive sensing and feedback systems, which enable transmission of multiple pieces of information. However, the integration of increasing numbers of feedback actuators and sensors causes a severe issue in terms of system complexity. In this work, we propose a pressure-sensing and feedback glove that enables multi-dimensional pressure sensing and feedback with a minimalist design of the functional units. The proposed glove consists of modular strain and pressure sensors based on films of liquid metal microchannels and coin vibrators. Strain sensors located at the finger joints can simultaneously project the bending motion of the individual joint into the virtual space or robotic hand. For subsequent tactile interactions, the design of two symmetrically distributed pressure sensors and vibrators at the fingertips possesses capabilities for multi-directional pressure sensing and feedback by evaluating the relationship of the signal variations between two sensors and tuning the feedback intensities of two vibrators. Consequently, both dynamic and static multi-dimensional pressure communication can be realized, and the vibrational actuation can be monitored by a liquid-metal-based sensor via a triboelectric sensing mechanism. A demonstration of object interaction indicates that the proposed glove can effectively detect dynamic force in varied directions at the fingertip while offering the reconstruction of a similar perception via the haptic feedback function. This device introduces an approach that adopts a minimalist design to achieve a multi-functional system, and it can benefit commercial applications in a more cost-effective way. Full article
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22 pages, 4195 KiB  
Article
Research on Stability Control Algorithm of Distributed Drive Bus under High-Speed Conditions
by Shaopeng Zhu, Bangxuan Wei, Chen Ping, Minjun Shi, Chen Wang, Huipeng Chen and Minglu Han
World Electr. Veh. J. 2023, 14(12), 343; https://doi.org/10.3390/wevj14120343 - 12 Dec 2023
Cited by 4 | Viewed by 2308
Abstract
Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is [...] Read more.
Aiming at the instability problem of a four-wheel independent drive electric bus under high-speed conditions, this paper first designs a vehicle yaw stability controller based on a linear two-degree-of-freedom model and a linear quadratic programming (LQR) algorithm. A vehicle roll stability controller is then designed based on a linear three-degree-of-freedom model and a model predictive control algorithm (MPC). Moreover, a coordinated control rule based on the lateral load transfer rate (LTR) is designed for the coupled problem of yaw and roll dynamics. Finally, the effectiveness of the proposed control algorithm is verified by simulation. The obtained results show that when the vehicle is running at a high speed of 90 km/h, the stability control algorithm can control the yaw rate tracking error within 0.05 rad/s. In addition, the control algorithm can reduce the maximum amplitude of the side slip angle, the maximum value of the roll angle, the maximum value of the roll angular velocity, and the amplitude of the lateral acceleration by more than 96%, 81.1%, 65.0%, and 11.1%, respectively. Full article
(This article belongs to the Special Issue Dynamics, Control and Simulation of Electrified Vehicles)
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13 pages, 905 KiB  
Article
Phenotypic and Genetic Analyses of In Vitro Embryo Production Traits in Chinese Holstein Cattle
by Yuechuan Huang, Hailiang Zhang, Cheng Mei, Minglu Yang, Shanjiang Zhao, Huabin Zhu and Yachun Wang
Animals 2023, 13(22), 3539; https://doi.org/10.3390/ani13223539 - 16 Nov 2023
Viewed by 1699
Abstract
Ovum pick up and in vitro embryo production (OPU-IVEP) is an essential technique in the dairy industry. The production efficiency of OPU-IVEP is significantly influenced by various factors, and phenotypic and genetic characteristics are highly variable in different populations. The objectives of this [...] Read more.
Ovum pick up and in vitro embryo production (OPU-IVEP) is an essential technique in the dairy industry. The production efficiency of OPU-IVEP is significantly influenced by various factors, and phenotypic and genetic characteristics are highly variable in different populations. The objectives of this study were (1) to reveal the phenotypic characteristics, including population distribution, and impacts of donor age and month on in vitro embryo production and (2) to estimate genetic parameters for five in vitro embryo production traits in Chinese Holstein cattle. A total of 7311 OPU-IVEP records of 867 Holstein heifers from August 2021 to March 2023 were collected in this study. Five in vitro embryo production traits were defined, including the number of cumulus–oocyte complexes (NCOC), the number of cleaved embryos (NCLV), the number of grade I embryos (NGE), and the proportion of NCLV to NCOC (PCLV) and NGE to NCOC (PGE). A univariate repeatability animal model was employed to estimate heritability and repeatability, and a bivariate repeatability animal model was employed to estimate the genetic correlations among five in vitro embryo production traits. It was found that the in vitro embryo production traits were significantly influenced by season, as the NGE and PGE were significantly decreased from June to August. In addition, the production efficiency of OPU-IVEP was also influenced by donor age. On the observed scale, the estimates of heritability were 0.33 for NCOC, 0.24 for NCLV, 0.16 for NGE, 0.06 for PCLV, and 0.10 for PGE, respectively. On the log-transformed scale, the estimates of heritability of NCOC, NCLV, and NGE were 0.34, 0.18, and 0.13. The genetic correlations among NCOC, NCLV, and NGE ranged from 0.61 (NCLV and NGE) to 0.95 (NCOC and NCLV), considering both scales. However, there were low genetic correlations between NCOC and proportion traits (PCLV and PGE) on both the observed scale and the log-transformed scale. In the end, the variation in Chinese Holstein cattle was found to be considerable. The EBV value and average NCOC, NGE, and PGE for the top 10% donors presented extreme differences to those for the bottom 10% donors for NCOC (24.02 versus 2.60), NGE (3.42 versus 0.36), and PGE (30.54% versus 3.46%). Overall, the results of this study reveal that in vitro embryo production traits are heritable with low to high heritability, and the count traits (NCOC, NCLV, and NGE) and proportion traits (PCLV and PGE) reflect different aspects of in vitro embryo production and should be incorporated into genetic selection for improving the embryo production efficiency of dairy cattle. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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18 pages, 7173 KiB  
Article
Microforce Sensing and Flexible Assembly Method for Key Parts of ICF Microtargets
by Tao Chen, Kejian Ni, Minglu Zhu and Lining Sun
Actuators 2023, 12(1), 1; https://doi.org/10.3390/act12010001 - 20 Dec 2022
Cited by 1 | Viewed by 1887
Abstract
Microassembly is one of the key techniques in various advanced industrial applications. Meanwhile, high success rates for axial hole assembly of thin-walled deep-cavity-type items remain a challenging issue. Hence, the flexible assembly approach of thin-walled deep-cavity parts is investigated in this study using [...] Read more.
Microassembly is one of the key techniques in various advanced industrial applications. Meanwhile, high success rates for axial hole assembly of thin-walled deep-cavity-type items remain a challenging issue. Hence, the flexible assembly approach of thin-walled deep-cavity parts is investigated in this study using the assembly of the key components, the microtarget component TMP (thermomechanical package) and the hohlraum in ICF (inertial confinement fusion) research, as examples. A clamping force-assembly force mapping model based on multisource microforce sensors was developed to overcome the incapacity of microscopic vision to properly identify the condition of components after contact. The ICF microtarget flexible assembly system, which integrates multisource microforce sensing and a six degrees of freedom micromotion sliding table, is presented to address the constraint that the standard microassembly approach is difficult to operate once the parts contact. This method can detect contact force down to the mN level, modify deviation of the component posture efficiently, and achieve nondestructive ICF microtarget assembly at the end. Full article
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17 pages, 7694 KiB  
Article
Analysis of Sequential Micromixing Driven by Sinusoidally Shaped Induced-Charge Electroosmotic Flow
by Haizhen Sun, Ziyi Li, Yongji Wu, Xinjian Fan, Minglu Zhu, Tao Chen and Lining Sun
Micromachines 2022, 13(11), 1985; https://doi.org/10.3390/mi13111985 - 16 Nov 2022
Cited by 6 | Viewed by 2088
Abstract
Multi-fluid micromixing, which has rarely been explored, typically represents a highly sought-after technique in on-chip biochemical and biomedical assays. Herein, we propose a novel micromixing approach utilizing induced-charge electroosmosis (ICEO) to implement multicomplex mixing between parallel streams. The variations of ICEO microvortices above [...] Read more.
Multi-fluid micromixing, which has rarely been explored, typically represents a highly sought-after technique in on-chip biochemical and biomedical assays. Herein, we propose a novel micromixing approach utilizing induced-charge electroosmosis (ICEO) to implement multicomplex mixing between parallel streams. The variations of ICEO microvortices above a sinusoidally shaped floating electrode (SSFE) are first investigated to better understand the microvortex development and the resultant mixing process within a confined channel. On this basis, a mathematical model of the vortex index is newly developed to predict the mixing degree along the microchannel. The negative exponential distribution obtained between the vortex index and mixing index demonstrates an efficient model to describe the mixing performance without solving the coupled diffusion and momentum equations. Specifically, sufficient mixing with a mixing index higher than 0.9 can be achieved when the vortex index exceeds 51, and the mixing efficiency reaches a plateau at an AC frequency close to 100 Hz. Further, a rectangle floating electrode (RFE) is deposited before SSFE to enhance the controlled sequence for three-fluid mixing. One side fluid can fully mix with the middle fluid with a mixing index of 0.623 above RFE in the first mixing stage and achieve entire-channel mixing with a mixing index of 0.983 above SSFE in the second mixing stage, thereby enabling on-demand sequential mixing. As a proof of concept, this work can provide a robust alternative technique for multi-objective issues and structural design related to mixers. Full article
(This article belongs to the Special Issue X-fluidics at the Micro/Nanoscale)
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40 pages, 8599 KiB  
Review
Progress in the Triboelectric Human–Machine Interfaces (HMIs)-Moving from Smart Gloves to AI/Haptic Enabled HMI in the 5G/IoT Era
by Zhongda Sun, Minglu Zhu and Chengkuo Lee
Nanoenergy Adv. 2021, 1(1), 81-120; https://doi.org/10.3390/nanoenergyadv1010005 - 19 Sep 2021
Cited by 79 | Viewed by 11393
Abstract
Entering the 5G and internet of things (IoT) era, human–machine interfaces (HMIs) capable of providing humans with more intuitive interaction with the digitalized world have experienced a flourishing development in the past few years. Although the advanced sensing techniques based on complementary metal-oxide-semiconductor [...] Read more.
Entering the 5G and internet of things (IoT) era, human–machine interfaces (HMIs) capable of providing humans with more intuitive interaction with the digitalized world have experienced a flourishing development in the past few years. Although the advanced sensing techniques based on complementary metal-oxide-semiconductor (CMOS) or microelectromechanical system (MEMS) solutions, e.g., camera, microphone, inertial measurement unit (IMU), etc., and flexible solutions, e.g., stretchable conductor, optical fiber, etc., have been widely utilized as sensing components for wearable/non-wearable HMIs development, the relatively high-power consumption of these sensors remains a concern, especially for wearable/portable scenarios. Recent progress on triboelectric nanogenerator (TENG) self-powered sensors provides a new possibility for realizing low-power/self-sustainable HMIs by directly converting biomechanical energies into valuable sensory information. Leveraging the advantages of wide material choices and diversified structural design, TENGs have been successfully developed into various forms of HMIs, including glove, glasses, touchpad, exoskeleton, electronic skin, etc., for sundry applications, e.g., collaborative operation, personal healthcare, robot perception, smart home, etc. With the evolving artificial intelligence (AI) and haptic feedback technologies, more advanced HMIs could be realized towards intelligent and immersive human–machine interactions. Hence, in this review, we systematically introduce the current TENG HMIs in the aspects of different application scenarios, i.e., wearable, robot-related and smart home, and prospective future development enabled by the AI/haptic-feedback technology. Discussion on implementing self-sustainable/zero-power/passive HMIs in this 5G/IoT era and our perspectives are also provided. Full article
(This article belongs to the Special Issue Recent Advances in Nanogenerators)
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14 pages, 7275 KiB  
Article
Feature Extraction for Bearing Fault Detection Using Wavelet Packet Energy and Fast Kurtogram Analysis
by Xiaojun Zhang, Jirui Zhu, Yaqi Wu, Dong Zhen and Minglu Zhang
Appl. Sci. 2020, 10(21), 7715; https://doi.org/10.3390/app10217715 - 31 Oct 2020
Cited by 24 | Viewed by 3094
Abstract
An integrated method for fault detection of bearing using wavelet packet energy (WPE) and fast kurtogram (FK) is proposed. The method consists of three stages. Firstly, several commonly used wavelet functions were compared to select the appropriate wavelet function for the application of [...] Read more.
An integrated method for fault detection of bearing using wavelet packet energy (WPE) and fast kurtogram (FK) is proposed. The method consists of three stages. Firstly, several commonly used wavelet functions were compared to select the appropriate wavelet function for the application of WPE. Then the analyzed signal is decomposed using WPE and the energy of each decomposed signal is calculated and selected for signal reconstruction. Secondly, the reconstructed signal is analyzed by FK to select the best central frequency and bandwidth for the band-pass filter. Finally, the filtered signal is processed using the squared envelope frequency spectrum and compared with the theoretical fault characteristic frequency for fault feature extraction. The procedure and performance of the proposed approach are illustrated and estimated by the simulation analysis, proving that the proposed method can effectively extract the weak transients. Moreover, the analysis results of gearbox bearing and rolling bearing cases show that the proposed method can provide more accurate fault features compared with the individual FK method. Full article
(This article belongs to the Special Issue Advances in Machine Fault Diagnosis)
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