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Experimental Study on the Performance and Emission of Chinese Small Agricultural Diesel Engine Fuelled with Methanol/Biodiesel/DTBP

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Journal of Harbin Institute of technology(New Series) 2022年第3期29卷 67-78页

作者： Ruina Li Liang Zhang Jialong Zhu Yan Hua Zhong Wang School of Automotive and Traffic Engineering Jiangsu UniversityZhenjiang 212013JiangsuChina Vehicle Measurement Control and Safety Key Laboratory of Sichuan ProvinceChengdu 610039China Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan Chengdu 610039China

Diesel engine alternative fuels, such as methanol and biodiesel, are beneficial to reduce diesel engine emission. In order to study the influence of methanol and biodiesel on the performance, economy and emission of small agricultural diesel engine, the physical-chemical properties(cetane number, lower heat value(LHV), viscosity, etc.) of methanol and biodiesel were analyzed. The methanol and biodiesel showed good complementary property to some extent. When a large proportion of methanol was added into biodiesel, the cetane number of the methanol/biodiesel blend will be greatly reduced. Since the cetane number of the blend fuel has great influence on the combustion process of diesel engine, after testing for blending ratio of methanol/biodiesel, the blend was prepared with 5%(BM5), 10%(BM10) and 15%(BM15) methanol, respectively. Di-Tert-Butyl Peroxide(DTBP) was chosen as a cetane number improver to be added into methanol/biodiesel blend. 0.25%, 0.50% and 0.75% of DTBP was added into BM15. The bench test was carried out on a 186 FA diesel engine to study the effect of methanol and DTBP on the engine performance and emissions. The results show that, at rated condition, compared with biodiesel, the NO;concentration of BM5, BM10 and BM15 is reduced by 5.02%, 33.85% and 21.24%, and smoke is reduced by 5.56%, 22.22% and 55.56%. However, the engine power is also reduced by 5.77%, 14.23% and 25.41%, and the brake specific energy consumption is increased by 3.31%, 7.78% and 6.37%. The addition of DTBP in methanol/biodiesel could recover the engine power to the level of diesel. DTBP shows good effect on the reduction of the brake specific energy consumption and NO_(x), CO, HC concentration, but a little increase of exhaust smoke.

关键词： methanol biodiesel agricultural diesel engine combustion performance emission

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A Lightweight Object Detection Network for Industrial Robot Based YOLOv5

A Lightweight Object Detection Network for Industrial Robot ...

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2023 China Automation Congress, CAC 2023

作者： Zhong, Tao Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

With the rapid development of deep learning, it has been widely applied in fields such as computer vision, natural language processing, and robotics. Despite the superior performance of deep learning in object detection, most industrial vision robots still rely on traditional object detection methods due to computational constraints of robot controllers. In order to improve the performance of object detection for vision robots, a lightweight 3D object detection network based on You Only Look Once version 5 (YOLOv5) is proposed for satisfying industrial production. YOLOv5 work to efficiently object detection using deep convolutional networks. In terms of model deployment, we adopt a novel OpenVINO-based model deployment approach. The OpenVINO framework significantly enhances the inference speed of models by model optimization and compression. Our model achieves a 70% reduction in inference time compared to the baseline model on CPU. The effectiveness of the proposed method is demonstrated through experiments. © 2023 IEEE.

关键词： Object detection

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An Improved YOLOv5 Detection Algorithm with Pruning and OpenVINO Quantization

An Improved YOLOv5 Detection Algorithm with Pruning and Open...

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2023 China Automation Congress, CAC 2023

作者： Chen, Cheng Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

In order to address the problem of current object detection models being too large to be deployed on robot controllers, this paper proposes improvements to YOLOv5 for real-time detection. The YOLOv5s model is pruned at the Batch Normalization (BN) layer, and further optimized using the OpenVINO tool for quantization. The results demonstrate that our improvements effectively improve the model's inference speed while maintaining its accuracy. Compared to the original YOLOv5 model, the pruned model achieves the same accuracy without degradation, with a 36.6% reduction in parameter count and a 35% reduction in weight storage file size. Furthermore, after optimization with OpenVINO, the final model achieves a FPS of 56. © 2023 IEEE.

关键词： Object detection

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A Real-time Cutting Model Based on Finite Element and Order Reduction

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Computer Systems Science & engineering 2022年第10期43卷 1-15页

作者： Xiaorui Zhang Wenzheng Zhang Wei Sun Hailun Wu Aiguo Song Sunil Kumar Jha Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

Telemedicine plays an important role in Corona Virus Disease 2019(COVID-19).The virtual surgery simulation system,as a key component in telemedicine,requires to compute in ***,this paper proposes a realtime cutting model based on finite element and order reduction method,which improves the computational speed and ensure the real-time *** proposed model uses the finite element model to construct a deformation model of the virtual ***,a model order reduction method combining proper orthogonal decomposition and Galerkin projection is employed to reduce the amount of deformation *** addition,the cutting path is formed according to the collision intersection position of the surgical instrument and the lesion area of the virtual ***,the Bezier curve is adopted to draw the incision outline after the virtual lung has been ***,the simulation system is set up on the PHANTOM OMNI force haptic feedback device to realize the cutting simulation of the virtual *** results show that the proposed model can enhance the real-time performance of telemedicine,reduce the complexity of the cutting simulation and make the incision smoother and more natural.

关键词： Virtual surgery cutting model finite element model model order reduction Bezier curve

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ResFFont: Few-Shot Font Generation based on Reversible Network 43

ResFFont: Few-Shot Font Generation based on Reversible Netwo...

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43rd Chinese control Conference, CCC 2024

作者： Ju, Chuanying Zhang, Ziying Chen, Xin China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China University of Geosciences School of Arts and Communication Wuhan430073 China

ISBN: (纸本)9789887581581

The technique of generating fonts with few-shot learning has become a popular research topic. The goal of this technique is to transform the source-to-target domain by using a small number of sample images to generate characters for new fonts. However, current research is limited by model frameworks and migration algorithms, which pose challenges for maintaining content integrity and stroke-level style consistency when generating Chinese characters. This paper proposes ResFFont, a reversible network-based model that uses a unique reversible framework and Global and Local Feature Fusion Module (GaLSFM) to ensure complete delivery of content information and stroke-level style consistency. The experimental results confirm the effectiveness and superiority of the ResFFont model, providing a new solution to the font generation problem. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Few-Shot Font Generation Reversible Network Style Transfer

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A Deep Reinforcement Learning-Based Multi-Objective Charging Scheduling Method for Electric Vehicle Charging Station

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IEEE Internet of Things Journal 2025年

作者： Zhao, Qiang Wu, Wenwei Cheng, Ningyu Guo, Ge Han, Yinghua Northeastern University at Qinhuangdao School of Control Engineering Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinghuangdao066004 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao066004 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Northeastern University at Qinhuangdao School of Computer and Communication Engineering Hebei Qinhuangdao066004 China

This paper investigates the charging scheduling problem within an Electric Vehicle Charging Station (EVCS), aiming to coordinate multiple charging piles to optimize the charging process. The objectives are to increase the profit for the Charging Station Operator (CSO) and enhance user satisfaction while mitigating significant fluctuations in grid load. However, since these objectives originate from different stakeholders, they are inherently conflicting;a strategy trained using fixed objective weights cannot satisfy all of them simultaneously. Additionally, uncertainties such as vehicle arrival and departure times, power requirements, and grid tariffs complicate the modeling of this process. To address these challenges, this paper reformulates the scheduling process as a Markov Decision Process (MDP) and proposes a novel model-free reinforcement learning method. By integrating randomly varying objective preferences into the inputs of agents, a set of policies corresponding to different objective preferences can be learned through a single training session. As a result, agents can execute various policies to satisfy the stakeholders’ needs based on these preferences. Moreover, a sampling adjustment strategy is introduced to improve the uniformity of the final non-dominated solution set and enhance the ability of the agent to explore the objective space. Experiments show that the proposed method can effectively solve the multi-objective problem of cooperative charging within an EVCS. Compared to the baseline method, the proposed method can achieve superior results while simultaneously reducing the computational cost to a significant extent. © 2014 IEEE.

关键词： Deep reinforcement learning

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Analysis of FAST' Best Working Paraboloid 3

Analysis of FAST' Best Working Paraboloid

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2022 3rd International Conference on Electrical, Electronic Information and communication engineering, EEICE 2022

作者： Xiao, Haitao Wang, Hanyun Li, Wenzhi Yang, Shanshan Dalian Scientific Test & Control Technology Institute PO Box67 Dalian116013 China School of Communication Engineering Jilin University Changchun130022 China

FAST consists of an active reflector, a signal receiving system (feedback source cabin) and other devices, where the reflector is an adjustable sphere composed of a main cable net, reflective panel, actuator and other main parts. It obtains an ideal paraboloid for operation in line with the position of the heavenly bodies, and meanwhile, a reflective panel regulating model by fitting the paraboloid as much as possible based on this ideal paraboloid, and calculates the absorptance of the cable according to the reflection model of electromagnetic waves. © Published under licence by IOP Publishing Ltd.

关键词： Cables

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Effective Methods to Improve the Accuracy of False Light Source Recognition in Visible Light Indoor Positioning

Effective Methods to Improve the Accuracy of False Light Sou...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： DeYue Zou LinNa Yan Siyu Gao Yunfeng Liu School of Information and Communication Engineering Dalian University of Technology Dalian China School of Intelligence & Electronic Engineering Dalian Neusoft University of Information Dalian China Beijing Institute of Control and Electronic Technology Dalian China

ISBN: (数字)9798350366402

ISBN: (纸本)9798350366419

With the development of visible light communication technology, visible light indoor positioning technology has become one of the research hotspots in indoor positioning technology. Visible light indoor positioning uses the light source information in the scene to locate the receiving end. However, the indoor environment is complex, and there are likely to be mirrors, glass and other reflective objects. These objects reflect to generate a pseudo-light source that transmits information similar to the actual light source, affecting the positioning result. Aiming at the recognition of pseudo-light sources, this paper adds classification steps to the algorithm based on chiral light source array, and proposes two methods that can improve the accuracy of identifying true and false light sources: K-Nearest Neighbor (KNN) classification and Weighted K-Nearest Neighbor (WKNN) classification and correction. Based on the chiral detection algorithm of vector product, we compare the success rates of the improved methods with the algorithm without the improved methods. The simulation results show that the accuracy of false detection can be further improved by adding the improved method, so as to improve the positioning accuracy.

关键词： Accuracy Simulation Indoor navigation Nearest neighbor methods Vectors Classification algorithms Reliability Mirrors Light sources Visible light communication

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Fault Diagnosis of Quadrotor UAV Propeller with Local-Global Attention-Based Graph Neural Networks

Fault Diagnosis of Quadrotor UAV Propeller with Local-Global...

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Data Driven control and Learning Systems (DDCLS)

作者： Zhiwei Wang Shaojun Liang Ye Sun Yi Yang Yanwei Wang Ying Zheng Belt and Road Joint Laboratory on Measurement and Control Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Ordnance Sergeant Army Engineering University Wuhan China School of Mechanical & Electrical Engineering Wuhan Institute of Technology Wuhan

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

With the wide application of Quadrotor Unmanned Aerial Vehicles (QUAV) in military and civilian fields, its flight reliability problem has become a hot research topic. The propellers, which are the important components relating to the performance of QUAV, play a central role in safe flight. Traditional data-driven fault diagnosis methods of QUAV are based on Euclidean distance, which cannot effectively capture the interrelationship of multiple variables. In this paper, we treat the fault diagnosis of QUAV propeller as a node classification problem in non-Euclidean infinite dimensional space by introducing the method of Local-Global Attention-based Graph Neural Network (LGA-GNN). First, the graph topology is constructed using the KNN method based on the real flight log of the QUAV. Then, the local and global attention strategies are integrated to form a graph-based collaborative feature extraction model. Finally, a unified end-to-end fault diagnosis framework tailored for QUAV is proposed. In the experiment section, real flight data of QUAV with different propeller fault conditions are collected, and the effectiveness and superiority of the proposed method are verified by comparing with other methods based on real data.

关键词： Fault diagnosis Learning systems Propellers Network topology Nearest neighbor methods Autonomous aerial vehicles Graph neural networks

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Remotely controllable Data Self-Destruction for Privacy-Preserving Sensitive Data Services 25

Remotely Controllable Data Self-Destruction for Privacy-Pres...

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25th IEEE International Conferences on High Performance Computing and communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhou, Chengxin Xue, Xianbin Riad, Khaled Zhu, Yan Chu, William Cheng-Chung School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North Navigation Control Technology Co. Ltd. Beijing China College of Computer Science and Information Technology King Faisal University Saudi Arabia Tunghai University Department of Computer Science Taichung Taiwan

ISBN: (纸本)9798350330014

This paper address a comprehensive solution to address data privacy and security challenges in data science, providing secure self-destruction of sensitive data, confidentiality through encryption, and flexible control over message destruction. Based on outsourcing cloud data services, we introduce a cloud retrograde storage (CRS) system for privacy-preserving self-destruction of sensitive data. The CRS is based on a frequently colliding hash table and recycle pool, and supports remote time, count, and range control. Hereby, we provide a remotely controllable mechanism for the prompt destruction of inactive messages against digital forensics without reducing the availability of services. The method used in the CRS involves storing messages in a recycle pool, where they are automatically erased at the end of their validity period or after being viewed by all recipients. The system also incorporates encryption and decryption processes to ensure confidentiality. The result of performance evaluation shows that the CRS effectively handles the destruction of messages and provides secure data removal from storage pools. The experiments demonstrate the efficiency and practicality of the CRS for large-scale data services. © 2023 IEEE.

关键词： Sensitive data

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