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信息融合 3

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传感引导；下肢外骨骼；人体传感网络；步态同步；体重支撑 1

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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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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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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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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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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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Magnetic confinement fusion: a brief review

Chuanjun HUANG, Laifeng LI

《能源前沿（英文）》 2018年第12卷第2期页码 305-313 doi: 10.1007/s11708-018-0539-1

摘要： Fusion energy is considered to be the ultimate energy source, which does not contribute to climate change compared with conventional fossil fuel. It is massive compared with unconventional renewable energy and demonstrates fewer safety features compared with unconventional fission energy. During the past several decades, never-ceasing efforts have been made to peacefully utilize the fusion energy in various approaches, especially inertial confinement and magnetic confinement. In this paper, the main developments of magnetic confinement fusion with emphasis on confinement systems as well as challenges of materials related to superconducting magnet and plasma-facing components are reviewed. The scientific feasibility of magnetic confinement fusion has been demonstrated in JET, TFTR, JT-60, and EAST, which instigates the construction of the International Thermonuclear Experimental Reactor (ITER). A fusion roadmap to DEMO and commercial fusion power plant has been established and steady progresses have been made to achieve the ultimate energy source.

关键词： fusion energy magnetic confinement tokamak structural material superconducting magnet

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Turbidity-adaptive underwater image enhancement method using image fusion

《机械工程前沿（英文）》 2022年第17卷第3期 doi: 10.1007/s11465-021-0669-8

摘要： Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

关键词： turbidity underwater image enhancement image fusion underwater robots visibility

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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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Biomedical sensor technologies on the platform of mobile phones

Lin LIU, Jing LIU

《机械工程前沿（英文）》 2011年第6卷第2期页码 160-175 doi: 10.1007/s11465-011-0216-0

摘要：

Biomedical sensors have been widely used in various areas of biomedical practices, which play an important role in disease detection, diagnosis, monitoring, treatment, health management, and so on. However, most of them and their related platforms are generally not easily accessible or just too expensive or complicated to be kept at home. As an alternative, new technologies enabled from the mobile phones are gradually changing such situations. As can be freely available to almost everyone, mobile phone offers a unique way to improve the conventional medical care through combining with various biomedical sensors. Moreover, the established systems will be both convenient and low cost. In this paper, we present an overview on the state-of-art biomedical sensors, giving a brief introduction of the fundamental principles and showing several new examples or concepts in the area. The focus was particularly put on interpreting the technical strategies to innovate the biomedical sensor technologies based on the platform of mobile phones. Some challenging issues, including feasibility, usability, security, and effectiveness, were discussed. With the help of electrical and mechanical technologies, it is expected that a full combination between the biomedical sensors and mobile phones will bring a bright future for the coming pervasive medical care.

关键词： biomedical sensor pervasive technology mobile phone combined system health management

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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

《信息与电子工程前沿（英文）》 2015年第16卷第3期页码 227-237 doi: 10.1631/FITEE.1400217

摘要： We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sampling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By compositing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best performance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

关键词： Compressive sensing (CS) Image fusion Gradient-based image fusion CS-based image fusion

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Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

《机械工程前沿（英文）》 2023年第18卷第1期 doi: 10.1007/s11465-022-0725-z

摘要： As parameter independent yet simple techniques, the energy operator (EO) and its variants have received considerable attention in the field of bearing fault feature detection. However, the performances of these improved EO techniques are subjected to the limited number of EOs, and they cannot reflect the non-linearity of the machinery dynamic systems and affect the noise reduction. As a result, the fault-related transients strengthened by these improved EO techniques are still subject to contamination of strong noises. To address these issues, this paper presents a novel EO fusion strategy for enhancing the bearing fault feature nonlinearly and effectively. Specifically, the proposed strategy is conducted through the following three steps. First, a multi-dimensional information matrix (MDIM) is constructed by performing the higher order energy operator (HOEO) on the analysis signal iteratively. MDIM is regarded as the fusion source of the proposed strategy with the properties of improving the signal-to-interference ratio and suppressing the noise in the low-frequency region. Second, an enhanced manifold learning algorithm is performed on the normalized MDIM to extract the intrinsic manifolds correlated with the fault-related impulses. Third, the intrinsic manifolds are weighted to recover the fault-related transients. Simulation studies and experimental verifications confirm that the proposed strategy is more effective for enhancing the bearing fault feature than the existing methods, including HOEOs, the weighting HOEO fusion, the fast Kurtogram, and the empirical mode decomposition.

关键词： higher order energy operator fault diagnosis manifold learning rolling element bearing information fusion

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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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Analysis of spinal lumbar interbody fusion cage subsidence using Taguchi method, finite element analysis

Christopher John NASSAU, N. Scott LITOFSKY, Yuyi LIN

《机械工程前沿（英文）》 2012年第7卷第3期页码 247-255 doi: 10.1007/s11465-012-0335-2

摘要：

Subsidence, when implant penetration induces failure of the vertebral body, occurs commonly after spinal reconstruction. Anterior lumbar interbody fusion (ALIF) cages may subside into the vertebral body and lead to kyphotic deformity. No previous studies have utilized an artificial neural network (ANN) for the design of a spinal interbody fusion cage. In this study, the neural network was applied after initiation from a Taguchi L₁₈ orthogonal design array. Three-dimensional finite element analysis (FEA) was performed to address the resistance to subsidence based on the design changes of the material and cage contact region, including design of the ridges and size of the graft area. The calculated subsidence is derived from the ANN objective function which is defined as the resulting maximum von Mises stress (VMS) on the surface of a simulated bone body after axial compressive loading. The ANN was found to have minimized the bone surface VMS, thereby optimizing the ALIF cage given the design space. Therefore, the Taguchi-FEA-ANN approach can serve as an effective procedure for designing a spinal fusion cage and improving the biomechanical properties.

关键词： anterior lumbar interbody fusion (ALIF) artificial neural network (ANN) finite element interbody cage lumbar interbody fusion subsidence taguchi method