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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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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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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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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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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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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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Big data and machine learning: A roadmap towards smart plants

《工程管理前沿（英文）》   页码 623-639 doi: 10.1007/s42524-022-0218-0

摘要： Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.

关键词： big data     machine learning     artificial intelligence     smart sensor     cyber–physical system     Industry 4.0     intelligent system     digitalization    

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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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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

《能源前沿（英文）》 doi: 10.1007/s11708-023-0912-6

摘要： With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energy sources (RESs) has become a trend in the industry. However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids. In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimization, and intraday real-time correction. The day-ahead optimization stage aims at the lowest operating cost, the rolling optimization stage aims at the lowest intraday economic cost, and the real-time correction aims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale optimization. The simulation results show that the economic loss is reduced by 19.6%, and the power fluctuation is decreased by 15.23%.

关键词： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed power supply     landscape uncertainty    

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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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Case study of data-oriented approach for building energy performance investigation

Jianjun XIA, He XIAO, Yi JIANG,

《能源前沿（英文）》 2010年 第4卷 第1期   页码 22-34 doi: 10.1007/s11708-010-0024-y

摘要： The key parameters that may influence building energy performance is studied by comparing the building energy data of college buildings in two different regions (the USA and China). By introducing data-orientated approach, a study of a set of on-campus building energy demand and consumption is conducted for cooling, heating and electricity. In addition, the heating, ventilation and air conditioning (HVAC) and lighting systems are studied in great detail. The breakdown analyses of the current energy consumption data are used to focus the investigation on critical issues. The analysis shows that the energy consumption of college buildings in the USA can be 3–5 times more than that of college buildings in China. The over-high energy consumption in campus buildings in the USA is mainly caused by operation schedule, system style, cooling and heating counteraction and sensor/actuator faults in the control systems, which also leads to the discussion of energy difference on the concept of “full control” or “local improvement” in building environment control. The study also indicates that the building energy efficiency can only be achieved by adjusting the demand according to natural conditions, encouraging green life behaviors, and developing relative technical solutions coordinated with the thrift culture and human behavior.

关键词： USA     counteraction     on-campus building     over-high     sensor/actuator    

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标题 作者 时间 类型 操作

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

期刊论文

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

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

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

期刊论文

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

期刊论文

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

Shahbaz Gul HASSAN,Murtaza HASAN,Daoliang LI

期刊论文

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

期刊论文

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

期刊论文

Big data and machine learning: A roadmap towards smart plants

期刊论文

基于互信息的水下无线传感器网络目标跟踪与加权融合

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

期刊论文

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

期刊论文

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

期刊论文

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

于宁波, 王石荣

期刊论文

Case study of data-oriented approach for building energy performance investigation

Jianjun XIA, He XIAO, Yi JIANG,

期刊论文