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Development and testing of a wireless smart toolholder with multi-sensor fusion

《机械工程前沿（英文）》 2023年第18卷第4期 doi: 10.1007/s11465-023-0774-y

摘要： The smart toolholder is the core component in the development of intelligent and precise manufacturing. It enables in situ monitoring of cutting data and machining accuracy evolution and has become a focal point in academic research and industrial applications. However, current table and rotational dynamometers for milling force, vibration, and temperature testing suffer from cumbersome installation and provide only a single acquisition signal, which limits their use in laboratory settings. In this study, we propose a wireless smart toolholder with multi-sensor fusion for simultaneous sensing of milling force, vibration, and temperature signals. We select force, vibration, and temperature sensors suitable for smart toolholder fusion to adapt to the cutting environment. Thereafter, structural design, circular runout, dynamic balancing, static stiffness, and dynamic inherent frequency tests are conducted to assess its dynamic and static performance. Finally, the smart toolholder is tested for accuracy and repeatability in terms of force, vibration, and temperature. Experimental results demonstrate that the smart toolholder accurately captures machining data with a relative deviation of less than 1.5% compared with existing force gauges and provides high repeatability of milling temperature and vibration signals. Therefore, it is a smart solution for machining condition monitoring.

关键词： wireless smart toolholder multi-sensor fusion circular runout dynamic balancing static stiffness dynamic inherent frequency

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Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

《机械工程前沿（英文）》 2022年第17卷第3期 doi: 10.1007/s11465-022-0692-4

摘要： Axial piston pumps have wide applications in hydraulic systems for power transmission. Their condition monitoring and fault diagnosis are essential in ensuring the safety and reliability of the entire hydraulic system. Vibration and discharge pressure signals are two common signals used for the fault diagnosis of axial piston pumps because of their sensitivity to pump health conditions. However, most of the previous fault diagnosis methods only used vibration or pressure signal, and literatures related to multi-sensor data fusion for the pump fault diagnosis are limited. This paper presents an end-to-end multi-sensor data fusion method for the fault diagnosis of axial piston pumps. The vibration and pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional neural network. Experiments were performed on an axial piston pump to confirm the effectiveness of the proposed method. Results show that the proposed multi-sensor data fusion method greatly improves the fault diagnosis of axial piston pumps in terms of accuracy and robustness and has better diagnostic performance than other existing diagnosis methods.

关键词： axial piston pump fault diagnosis convolutional neural network multi-sensor data fusion

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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

《机械工程前沿（英文）》 2023年第18卷第2期 doi: 10.1007/s11465-022-0736-9

摘要： Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of machines. Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the fault diagnosis field. However, existing studies suffer from two weaknesses. First, the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault types. Second, the localization for multi-source faults is seldom investigated, although locating the anomaly variable over multivariate sensing data for certain types of faults is desirable. This article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations (MSRs). First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition results. Second, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault sources are therefore determined. The proposed method is demonstrated by experiments on an induction motor and a centrifugal pump. Results show the proposed method’s validity in diagnosing fault types and sources.

关键词： fault recognition fault localization multi-sensor relations network analysis graph neural network

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基于多传感器融合的智能车在野外环境中的障碍物检测研究 Review

胡劲文,郑博尹,王策,赵春晖,侯晓磊,潘泉,徐钊

《信息与电子工程前沿（英文）》 2020年第21卷第5期页码 649-808 doi: 10.1631/FITEE.1900518

摘要：随着传感器融合技术发展，人们对智能地面车辆进行大量研究，其中障碍物检测是一个关键技术。障碍物检测是一项复杂任务，涉及多种障碍物、传感器特性和环境条件。虽然道路驾驶员辅助系统或自动驾驶系统已得到充分研究，但是为城市场景结构化道路开发的方法应用于野外环境时，可能因不确定性和多样性而失效。单一类型传感器由于感受范围、信号特征和检测环境的限制，难以满足障碍物检测需求，这促使研究人员和工程师开发多传感器融合方法和系统集成。该综述旨在总结野外环境中智能地面车辆的车载多传感器配置的主要考虑事项，为用户提供根据性能要求和应用环境选择传感器的指南。本文回顾了最新多传感器融合方法和系统原型，将其与对应的异构传感器配置相关联，讨论了新兴技术和面临的挑战。

关键词：多传感器融合；障碍物检测；野外环境；智能车；无人驾驶地面车辆

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Development of temperature-robust damage factor based on sensor fusion for a wind turbine structure

Jong-Woong PARK,Sung-Han SIM,Jin-Hak YI,Hyung-Jo JUNG

《结构与土木工程前沿（英文）》 2015年第9卷第1期页码 42-47 doi: 10.1007/s11709-014-0285-3

摘要： Wind power systems have gained much attention due to the relatively high reliability, maturity in technology and cost competitiveness compared to other renewable alternatives. Advances have been made to increase the power efficiency of the wind turbines while less attention has been focused on structural integrity assessment of the structural systems. Vibration-based damage detection has widely been researched to identify damages on a structure based on change in dynamic characteristics. Widely spread methods are natural frequency-based, mode shape-based, and curvature mode shape-based methods. The natural frequency-based methods are convenient but vulnerable to environmental temperature variation which degrades damage detection capability; mode shapes are less influenced by temperature variation and able to locate damage but requires extensive sensor instrumentation which is costly and vulnerable to signal noises. This study proposes novelty of damage factor based on sensor fusion to exclude effect of temperature variation. The combined use of an accelerometer and an inclinometer was considered and damage factor was defined as a change in relationship between those two measurements. The advantages of the proposed method are: 1) requirement of small number of sensor, 2) robustness to change in temperature and signal noise and 3) ability to roughly locate damage. Validation of the proposed method is carried out through numerical simulation on a simplified 5 MW wind turbine model.

关键词： sensor fusion damage detection structural health monitoring

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Information fusion in aquaculture: a state-of the art review

Shahbaz Gul HASSAN,Murtaza HASAN,Daoliang LI

《农业科学与工程前沿（英文）》 2016年第3卷第3期页码 206-221 doi: 10.15302/J-FASE-2016111

摘要： Efficient fish feeding is currently one of biggest challenges in aquaculture to enhance the production of fish quality and quantity. In this review, an information fusion approach was used to integrate multi-sensor and computer vision techniques to make fish feeding more efficient and accurate. Information fusion is a well-known technology that has been used in different fields of artificial intelligence, robotics, image processing, computer vision, sensors and wireless sensor networks. Information fusion in aquaculture is a growing field of research that is used to enhance the performance of an “industrialized” ecosystem. This review study surveys different fish feeding systems using multi-sensor data fusion, computer vision technology, and different food intake models. In addition, different fish behavior monitoring techniques are discussed, and the parameters of water, pH, dissolved oxygen, turbidity, temperature etc., necessary for the fish feeding process, are examined. Moreover, the different waste management and fish disease diagnosis techniques using different technologies, expert systems and modeling are also reviewed.

关键词： aquaculture computer vision information fusion modeling sensor

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Contact detection with multi-information fusion for quadruped robot locomotion under unstructured terrain

《机械工程前沿（英文）》 2023年第18卷第3期 doi: 10.1007/s11465-023-0760-4

摘要： Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments. To improve the reliability and accuracy of contact detection for quadruped robots, a detection approach based on the probabilistic contact model with multi-information fusion is presented to detect the actual contact states of robotic feet with the ground. Moreover, a relevant control strategy to address unexpected early and delayed contacts is planned. The approach combines the internal state information of the robot with the measurements from external sensors mounted on the legs and feet of the prototype. The overall contact states are obtained by the classification of the model-based predicted probabilities. The control strategy for unexpected foot-to-ground contacts can correct the control actions of each leg of the robot to traverse cluttered environments by changing the contact state. The probabilistic model parameters are determined by testing on the single-leg experimental platform. The experiments are conducted on the experimental prototype, and results validate the contact detection and control strategy for unexpected contacts in unstructured terrains during walking and trotting. Compared with the body orientation under the time-based control method regardless of terrain, the root mean square errors of roll, pitch, and yaw respectively decreased by 60.07%, 54.73%, and 64.50% during walking and 73.40%, 61.49%, and 61.48% during trotting.

关键词： multi-information fusion contact detection quadruped robot probabilistic contact model unstructured terrain

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M-LFM: a multi-level fusion modeling method for shape−performance integrated digital twin of complex

《机械工程前沿（英文）》 2022年第17卷第4期 doi: 10.1007/s11465-022-0708-0

摘要： As a virtual representation of a specific physical asset, the digital twin has great potential for realizing the life cycle maintenance management of a dynamic system. Nevertheless, the dynamic stress concentration is generated since the state of the dynamic system changes over time. This generation of dynamic stress concentration has hindered the exploitation of the digital twin to reflect the dynamic behaviors of systems in practical engineering applications. In this context, this paper is interested in achieving real-time performance prediction of dynamic systems by developing a new digital twin framework that includes simulation data, measuring data, multi-level fusion modeling (M-LFM), visualization techniques, and fatigue analysis. To leverage its capacity, the M-LFM method combines the advantages of different surrogate models and integrates simulation and measured data, which can improve the prediction accuracy of dynamic stress concentration. A telescopic boom crane is used as an example to verify the proposed framework for stress prediction and fatigue analysis of the complex dynamic system. The results show that the M-LFM method has better performance in the computational efficiency and calculation accuracy of the stress prediction compared with the polynomial response surface method and the kriging method. In other words, the proposed framework can leverage the advantages of digital twins in a dynamic system: damage monitoring, safety assessment, and other aspects and then promote the development of digital twins in industrial fields.

关键词： shape−performance integrated digital twin (SPI-DT) multi-level fusion modeling (M-LFM) surrogate model telescopic boom crane data fusion

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A cellphone-based colorimetric multi-channel sensor for water environmental monitoring

《环境科学与工程前沿（英文）》 2022年第16卷第12期 doi: 10.1007/s11783-022-1590-z

摘要：

● A cellphone-based colorimetric multi-channel sensor for in-field detection.

关键词： Colorimetric analysis Multi-channel sensor Cellphone Water quality indexes Environmental monitoring

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基于互信息的水下无线传感器网络目标跟踪与加权融合 None

Duo ZHANG, Mei-qin LIU, Sen-lin ZHANG, Zhen FAN, Qun-fei ZHANG

《信息与电子工程前沿（英文）》 2018年第19卷第4期页码 544-556 doi: 10.1631/FITEE.1601695

摘要：水下无线传感器网络为水下目标跟踪问题提供了可靠有效支持，但水下网络能量和带宽资源有限，只能选择一部分节点参与跟踪任务。融合中心通过收集、融合各个传感器发送的量测进行目标跟踪，因此设计更好的融合权值极为重要。针对水下目标跟踪中的加权融合问题，首先通过计算量测与目标状态之间的互信息，利用互信息衡量融合权重；其次利用互信息融合权重设计一种新的多传感器加权粒子滤波算法，利用克拉美罗（Cramer-Rao）下界设计节点选择方案，以提高跟踪算法效率；最后通过仿真实验对算法进行验证。仿真结果表明，通过选择合适融合权值，目标状态估计精度显著提高。

关键词：目标跟踪；加权融合；互信息；节点选择；水下无线传感器网络

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A thermally flexible and multi-site tactile sensor for remote 3D dynamic sensing imaging

Guoting Xia, Yinuo Huang, Fujiang Li, Licheng Wang, Jinbo Pang, Liwei Li, Kai Wang

《化学科学与工程前沿（英文）》 2020年第14卷第6期页码 1039-1051 doi: 10.1007/s11705-019-1901-5

摘要： A flexible, multi-site tactile and thermal sensor (MTTS) based on polyvinylidene fluoride (resolution 50 × 50) is reported. It can be used to implement spatial mapping caused by tactile and thermal events and record the two-dimensional motion trajectory of a tracked target object. The output voltage and current signal are recorded as a mapping by sensing the external pressure and thermal radiation stimulus, and the response distribution is dynamically observed on the three-dimensional interface. Through the mapping relationship between the established piezoelectric and pyroelectric signals, the piezoelectric component and the pyroelectric component are effectively extracted from the composite signals. The MTTS has a good sensitivity for tactile and thermal detection, and the electrodes have good synchronism. In addition, the signal interference is less than 9.5% and decreases as the pressure decreases after the distance between adjacent sites exceeds 200 µm. The integration of MTTS and signal processing units has potential applications in human-machine interaction systems, health status detection and smart assistive devices.

关键词： tactile/thermal sensor piezoelectric/pyroelectric effects high resolution spatial mapping motion monitoring

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通过双RGB-D传感器融合增强对未知环境的自主探索和地图绘制 Article

于宁波, 王石荣

《工程（英文）》 2019年第5卷第1期页码 164-172 doi: 10.1016/j.eng.2018.11.014

摘要：

对未知环境的自主探索和地图构建具有广泛的应用价值和重要的现实意义。现有方法多采用距离传感器生成二维栅格地图。红/ 绿/ 蓝深度（red/green/blue-depth，RGB-D）传感器提供环境的颜色和深度信息，从而生成三维（three-dimensional，3D）点云地图，便于人类直观感知。本文提出了一种利用双RGB-D 传感器实现未知室内环境自动探测和测绘的系统方法。通过同步处理RGB-D数据，生成定位点，逐步构建三维点云图和二维栅格地图。紧接着，探索方法被建模为一个部分可观测的马尔科夫决策过程，将局部地图推演和全局边界搜索方法相结合进行自主探索，将动态行为约束用于运动控制。这有效避免了局部最优，保证了探测效果。在单连通和多分支区域的实验表明，该方法具有较好的鲁棒性和较高的效率。

关键词：自主探索 RGB-D 传感器融合点云局部地图推演全局边界搜索

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基于融合任务信息图神经网络的多智能体系统协同规划 Research Article

戴汉奇1,2,芦维宁2,李祥隆3,杨君1,孟德山4,刘衍泽5,梁斌1

《信息与电子工程前沿（英文）》 2022年第23卷第7期页码 1069-1076 doi: 10.1631/FITEE.2100597

摘要：协同规划是多智能体系统博弈领域的关键问题之一。本文聚焦每个智能体只有一个局部观测范围和局部通信情况下的协作规划。提出一种新型协同规划框架，该框架将图神经网络与融合任务信息采样方法相结合。本文的两个主要贡献是基于与前期工作的比较：（1）使用图采样与聚合方法（GraphSAGE）实现动态近邻智能体信息融合，这是该方法首次用于处理协同规划问题；（2）提出一种面向任务的采样方法，从特定方向聚合知识，使所提模型获得高效、稳定的训练过程。实验结果证明了所提方法的有效性。

关键词：多智能体系统；协同规划；图采样与聚合（GraphSAGE）；融合任务信息

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基于遗传算法的传感器网络拓扑控制研究

刘林峰,庄艳艳,刘业

《中国工程科学》 2008年第10卷第2期页码 66-71

摘要：

无线传感器网络的首要设计目标是延长网络生命期，网络的拓扑控制是实现这一目标的支撑基础。针对传统拓扑控制方案所获拓扑的连通冗余度高或结构健壮性低等弊端，将问题转化为多判据最小生成树模型，提出了一种基于遗传算法的拓扑控制方案。仿真实验结果表明，该方案可获得具有网络整体功耗低、结构健壮性高和节点间通信干扰小等特点的拓扑结构，因而能够有效地延长传感器网络生命期。

关键词：无线传感器网络拓扑控制多判据最小生成树问题遗传算法

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一种面向地面区域检测和目标跟踪的多传感器系统协同调度方法 Research Article

张昀普,付强,单甘霖

《信息与电子工程前沿（英文）》 2023年第24卷第2期页码 245-258 doi: 10.1631/FITEE.2200121

摘要：本文提出一种面向多任务协同的多传感器系统协同调度方法，并将其应用于地面区域检测和目标跟踪。调度的目的是选择最佳的传感器来完成分配的作战任务，并获得最佳作战收益。首先建立区域检测模型，并提出检测风险的计算方法以量化在调度中的检测收益。然后结合道路约束信息和多普勒盲区信息建立地面目标跟踪模型，并引入后验克拉美罗下限评估未来时刻的跟踪精度。最后，考虑检测、跟踪和能耗控制的需求建立目标函数，通过求解目标函数，得到最优的传感器调度方案。仿真结果表明，所提传感器调度方法可以选择合适的传感器完成所需作战任务，并在区域检测、目标跟踪和能耗控制方面均具有良好性能。

关键词：传感器调度；区域检测；目标跟踪；道路约束；多普勒盲区

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标题作者时间类型操作

Development and testing of a wireless smart toolholder with multi-sensor fusion

期刊论文

Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

期刊论文

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

期刊论文

基于多传感器融合的智能车在野外环境中的障碍物检测研究

胡劲文,郑博尹,王策,赵春晖,侯晓磊,潘泉,徐钊

期刊论文