Zude Zhou

Wuhan University of Technology, Wu-han-shih, Hubei, China

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Publications (130)103.06 Total impact

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    ABSTRACT: A fiber Bragg grating (FBG) sensing based triaxial vibration sensor has been presented in this paper. The optical fiber is directly employed as elastomer, and the triaxial vibration of a measured body can be obtained by two pairs of FBGs. A model of a triaxial vibration sensor as well as decoupling principles of triaxial vibration and experimental analyses are proposed. Experimental results show that: sensitivities of 86.9 pm/g, 971.8 pm/g and 154.7 pm/g for each orthogonal sensitive direction with linearity are separately 3.64%, 1.50% and 3.01%. The flat frequency ranges reside in 20-200 Hz, 3-20 Hz and 4-50 Hz, respectively; in addition, the resonant frequencies are separately 700 Hz, 40 Hz and 110 Hz in the x/y/z direction. When the sensor is excited in a single direction vibration, the outputs of sensor in the other two directions are consistent with the outputs in the non-working state. Therefore, it is effectively demonstrated that it can be used for three-dimensional vibration measurement.
    Sensors 09/2015; 15(9):24214-24229. DOI:10.3390/s150924214 · 2.25 Impact Factor
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    ABSTRACT: In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic Bees Algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems.
    Computational Intelligence and Neuroscience 09/2015; 2015(7):780352. DOI:10.1155/2015/780352 · 0.60 Impact Factor
  • International Journal of Advanced Manufacturing Technology 09/2015; DOI:10.1007/s00170-015-7738-2 · 1.46 Impact Factor
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    ABSTRACT: There is a growing need of knowledge description of manufacturing equipment and their capabilities for users, in order to efficiently obtain the on-demand services of manufacturing equipment in cloud manufacturing, and the understanding of the manufacturing capability of equipment is the most important basis for optimizing the cloud service management. During the manufacturing processes, a number of uncertain incidents may occur, which could degrade the manufacturing system performance or even paralyze the production line. Hence, all aspects about the equipment should be reflected within the knowledge description, and the static and dynamic information are both included in the knowledge model of manufacturing equipment. Unification and dynamics are the most important characteristics of the framework of knowledge description. The primary work of this study is fourfold. First, three fundamental ontologies are built, namely, basic information ontology, functional ontology, and manufacturing process ontology. Second, the correlation between the equipment ontology and the fundamental ontology that forms the unified description framework is determined. Third, the mapping relationship between the real-time condition data and the model of manufacturing equipment capability ontology is established. On the basis of the mapping relationship, the knowledge structure of the manufacturing equipment capability ontology is able to update in real-time. Finally, a prototype system is developed to validate the feasibility of the proposed dynamic modeling method. The system implementation demonstrates that the proposed knowledge description framework and method are capable of reflecting the current conditions and the dynamic capability of manufacturing equipment.
    Journal of Manufacturing Science and Engineering 08/2015; 137(4). DOI:10.1115/1.4030079 · 1.02 Impact Factor
  • Tianliang Li · Yuegang Tan · Zude Zhou · Qin Wei
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    ABSTRACT: A pasted type distributed two-dimensional fiber Bragg grating (FBG) vibration sensor has been proposed and studied in this paper. The optical fiber is directly considered as an elastomer. The two-dimensional vibration can be separated by subtraction/addition of two FBGs' center wavelength shift. The principle of the sensor as well as numerical simulation and experimental analyses are presented. Experimental results show that the resonant frequencies of the sensor x/y main vibration direction are separately 1300/20.51 Hz, which are consistent with the numerical simulation analysis result. The flat frequency range resides in 10-750 Hz and 3-12 Hz, respectively; dynamic range is 28.63 dB; in the x main vibration direction, the sensor's sensitivity is 32.84 pm/g, with linearity 3.91% in the range of 10-60 m/s(2), while in the y main vibration direction, the sensor's sensitivity is 451.3 pm/g, with linearity 1.92% in the range of 1.5-8 m/s(2). The cross sensitivity is 3.91%. Benefitting from the two dimensional sensing properties, it can be used in distributed two-dimensional vibration measurement.
    The Review of scientific instruments 07/2015; 86(7):075009. DOI:10.1063/1.4927456 · 1.61 Impact Factor
  • Tianliang Li · Yuegang Tan · Zude Zhou · Li Cai · Lai Wei
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    ABSTRACT: This paper has presented a non-contact vibration sensor based on fiber Bragg grating (FBG) sensing, and applied to measure vibration of turbine rotor dynamic balance platform. The principle of the sensor has been introduced; it’s based on magnetic coupling principle and the FBG sensing to obtain the vibration. The sensors calibration experiments show that: sensitivity of 1st sensor in range of 3.00-3.80mm is -449.83pm/mm, linearity is 5.19%; sensitivity of 2nd sensor in range of 4.00-5.00mm is -430.95pm/mm, linearity is 3.31%. In addition, turbine rotor dynamic vibration detection system based on eddy current displacement sensor and non-contact FBG vibration sensor have set; and contrast analysis of experiments data shows that: the vibration signal analysis of non-contact FBG vibration sensor is basically the same as the result of eddy current displacement sensor. It verified that the sensor can be used for non-contact measurement of turbine rotor dynamic balance vibration.
    IEICE Electronics Express 06/2015; 12(12). DOI:10.1587/elex.12.20150380 · 0.32 Impact Factor
  • Chunsheng Song · Shengquan Xie · Zude Zhou · Yefa Hu
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    ABSTRACT: Pneumatic Artificial Muscle (PAM) actuator has been widely used in medical and rehabilitation robots, owing to its high power-to-weight ratio and inherent safety characteristics. However, the PAM exhibits highly non-linear and time variant behavior, due to compressibility of air, use of elastic-viscous material as core tube and pantographic motion of the PAM outer sheath. It is difficult to obtain a precise model using analytical modeling methods. This paper proposes a new Artificial Neural Network (ANN) based modeling approach for modeling PAM actuator. To obtain higher precision ANN model, three different approaches, namely, Back Propagation (BP) algorithm, Genetic Algorithm (GA) approach and hybrid approach combing BP algorithm with Modified Genetic Algorithm (MGA) are developed to optimize ANN parameters. Results show that the ANN model using the GA approach outperforms the BP algorithm, and the hybrid approach shows the best performance among the three approaches.
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    ABSTRACT: Temperature is one of the most significant parameters influencing heavy-duty machine tool accuracy. In order to model the correlation between temperature field distribution and thermally induced deformation, and compensate thermal errors, it is critical to obtain the temperature field variations of a precision machine tool in real-time. In this paper, based on fiber Bragg grating (FBG) sensing technology, a novel method for measuring real-time temperature field of a heavy-duty machine tool is presented and the spindle thermal shift error is analyzed. Measurement experiments of real-time temperature field and thermal shift error were carried out on a CNC turn-milling machine tool in shop floor. The variations of ambient and surface temperatures were obtained by the proposed system and the spindle thermal shift errors were monitored by laser displacement sensors at the same time. Experimental results indicate that the surface temperature variations distributed over the machine structure are non-uniform, and the surface temperature field and spindle thermal error have a similar change trend following the ambient temperature. The proposed real-time measurement system could be utilized to analyze the thermal behavior and improve the accuracy of heavy-duty machine tools.
    Mechatronics 05/2015; DOI:10.1016/j.mechatronics.2015.04.004 · 1.73 Impact Factor
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    ABSTRACT: Robot-assisted rehabilitation and therapy has become more and more frequently used to help the elderly, disabled patients or movement disorders to perform exercise and training. The field of robot-assisted lower limb rehabilitation has rapidly evolved in the last decade. This article presents a review on the most recent progress (from year 2001 to 2014) of mechanisms, training modes and control strategies for lower limb rehabilitation robots. Special attention is paid to the adaptive robot control methods considering hybrid data fusion and patient evaluation in robot-assisted passive and active lower limb rehabilitation. The characteristics and clinical outcomes of different training modes and control algorithms in recent studies are analysed and summarized. Research gaps and future directions are also highlighted in this paper to improve the outcome of robot-assisted rehabilitation.
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    ABSTRACT: Milling force is an important parameter to describe the mechanical processing chip removal process, and it has a direct influence on generation of heat, tool wear or failure, quality of machined surface and accuracy of the work piece. Its accurate measurement is a significant basis for judging process state and improving the reliability of machining system. In this study, through analyzing the variation rule of ring diameter, a new method that using Fiber Bragg grating sensors and variation rule of ring diameter to measure the milling force has been proposed, and the basic structure of annulus has also been designed. A dynamometer has also been constructed, and the preliminary verification test was done. Through the analysis of experimental data, the dynamometer based on annulus elastic body can be used in milling force test, and it owns high sensitivity.
    Mechatronics 04/2015; DOI:10.1016/j.mechatronics.2015.03.007 · 1.73 Impact Factor
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    ABSTRACT: A non-contact vibration sensor based on the fiber Bragg grating (FBG) sensor has been presented, and it is used to monitor the vibration of rotating shaft. In the paper, we describe the principle of the sensor and make some experimental analyses. The analysis results show that the sensitivity and linearity of the sensor are -1.5 pm/um and 4.11% within a measuring range of 2 mm-2.6 mm, respectively. When it is used to monitor the vibration of the rotating shaft, the analysis signals of vibration of the rotating shaft and the critical speed of rotation obtained are the same as that obtained from the eddy current sensor. It verifies that the sensor can be used for the non-contact measurement of vibration of the rotating shaft system and for fault monitoring and diagnosis of rotating machinery.
    Photonic Sensors 01/2015; 5(2). DOI:10.1007/s13320-015-0220-9
  • Tianliang Li · Yuegang Tan · Zude Zhou · Li Cai · Ruiya Li
    IEICE Electronics Express 01/2015; DOI:10.1587/elex.12.20150583 · 0.32 Impact Factor
  • Fan Zhang · Zude Zhou · Wenjun Xu
    10/2014; 9(10). DOI:10.4304/jsw.9.10.2598-2606
  • Sensor Review 08/2014; 34(4):343-348. DOI:10.1108/SR-09-2013-728 · 0.74 Impact Factor
  • Wei Meng · Quan Liu · Zude Zhou · Qingsong Ai
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    ABSTRACT: Purpose: The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control scheme for parallel robot-assisted lower limb rehabilitation and training. Design/methodology/approach: An active interaction control strategy based on EMG motion recognition and adaptive impedance model is implemented on a six-degrees of freedom parallel robot for lower limb rehabilitation. The autoregressive coefficients of EMG signals integrating with a support vector machine classifier are utilized to predict the movement intention and trigger the robot assistance. An adaptive impedance controller is adopted to influence the robot velocity during the exercise, and in the meantime, the user's muscle activity level is evaluated online and the robot impedance is adapted in accordance with the recovery conditions. Findings: Experiments on healthy subjects demonstrated that the proposed method was able to drive the robot according to the user's intention, and the robot impedance can be updated with the muscle conditions. Within the movement sessions, there was a distinct increase in the muscle activity levels for all subjects with the active mode in comparison to the EMG-triggered mode. Originality/value: Both users' movement intention and voluntary participation are considered, not only triggering the robot when people attempt to move but also changing the robot movement in accordance with user's efforts. The impedance model here responds directly to velocity changes, and thus allows the exercise along a physiological trajectory. Moreover, the muscle activity level depends on both the normalized EMG signals and the weight coefficients of involved muscles.
    Industrial Robot 08/2014; 41(5):465-479. DOI:10.1108/IR-04-2014-0327 · 0.64 Impact Factor
  • Quan Liu · Dong Liu · Wei Meng · Zude Zhou · Qingsong Ai
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    ABSTRACT: Multi-degrees of freedom (DOF) parallel robot, due to its compact structure and high operation accuracy, is a promising candidate for medical rehabilitation devices. However, its controllability relating to the nonlinear characteristics challenges its interaction with human subjects during the rehabilitation process. In this paper, we investigated the control of a parallel robot system using fuzzy sliding mode control (FSMC) for constructing a simple controller in practical rehabilitation, where a fuzzy logic system was used as the additional compensator to the sliding mode controller (SMC) for performance enhancement and chattering elimination. The system stability is guaranteed by the Lyapunov stability theorem. Experiments were conducted on a lower limb rehabilitation robot, which was built based on kinematics and dynamics analysis of the 6-DOF Stewart platform. The experimental results showed that the position tracking precision of the proposed FSMC is sufficient in practical applications, while the velocity chattering had been effectively reduced in comparison with the conventional FSMC with parameters tuned by fuzzy systems.
    International Journal of Humanoid Robotics 04/2014; 11(01). DOI:10.1142/S0219843614500042 · 0.69 Impact Factor
  • Yong Yin · Yu Li · Chaoyong Zhang · Ping Lou · Zude Zhou
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    ABSTRACT: As the future development trend of advanced manufacturing technologies, manufacturing grid (MG) is attracting more and more interests, and massive results have been achieved. However, as current existing service MG platforms are based on different standards and specifications, access to manufacturing resources of these platforms remains incompatible. To enhance the adaptability of MG with different standards, a uniform manufacturing resource service adapter for MG called uniform service adapter (UA) is suggested. Firstly, existing service access mechanisms of current MG are analyzed briefly. Then the frameworks of UA, which are composed of three parts, namely the service adapter, the data management adapter, and the binding adapter, is presented. Next, each part of UA is realized in detail. Lastly, a simple test scene of UA is provided. The UA introduced in the paper can accommodate the dynamics, complexity, and heterogeneity of the situation, providing a uniform interface for the upper applications to overcome the incompatibility of the services with different standards.
    International Journal of Advanced Manufacturing Technology 04/2014; 72(1-4):221-230. DOI:10.1007/s00170-014-5631-z · 1.46 Impact Factor
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    ABSTRACT: A non-contact vibration sensor based on fiber Bragg grating (FBG) sensing has been proposed and studied in this paper. The principle of the sensor as well as simulation and experimental analyses are introduced. When the distance between the movable head and the measured shaft changed, the diaphragm deformed under magnetic coupling of the permanent magnet on the measured magnetic shaft. As a result, the center wavelength of the FBG connected to the diaphragm changed, based on which the vibration displacement of the rotating shaft could be obtained. Experimental results show that the resonant frequency of the sensor is about 1500 Hz and the working band ranges within 0-1300 Hz, which is consistent with the simulation analysis result; the sensitivity is -1.694 pm/μm and the linearity is 2.92% within a range of 2-2.4 mm. It can be used to conduct non-contact measurement on the vibration of the rotating shaft system.
    The Review of scientific instruments 02/2014; 85(1):015002. DOI:10.1063/1.4857755 · 1.61 Impact Factor
  • Fan Zhang · Zude Zhou · Wenjun Xu
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    ABSTRACT: Fiber Bragg Grating (FBG) sensor network has attracted more attention in online condition monitoring for the large mechanical equipment. By the efforts of the encoding scheme for sensor nodes, the capacity for the distributed FBG sensor network can be significantly improved. However, due to the increasing number of sensor nodes, the precision of tracking and locating for the FBG sensors has become a bottleneck that should be conquered. In order to realize more accurate and comprehensive condition monitoring for the large mechanical equipment, an enhanced tracking algorithm for distributed encoding FBG sensor network is presented. The novel tracking algorithm uses three classes of progressive intelligent processing approaches, including the improved cycle matching method, the secondary filter intelligent disposal method, and the assistant decision processes method, to conquer the limitations of the traditional tracking algorithm in which the chaos and error results would be caused as the sensor information variations are overlapped. A set of experiments has been conducted and the results demonstrate that the proposed tracking algorithm performs better than the traditional algorithm in location accuracy for the distributed encoding FBG sensor network and can effectively operate in various working conditions of the large mechanical equipment.
    International Journal of Distributed Sensor Networks 01/2014; 2014:1-13. DOI:10.1155/2014/823029 · 0.67 Impact Factor

Publication Stats

480 Citations
103.06 Total Impact Points


  • 2004–2015
    • Wuhan University of Technology
      Wu-han-shih, Hubei, China
  • 2003–2009
    • Huazhong University of Science and Technology
      • • State Engineering Research Center of Numerical Control System
      • • School of Mechanical Science and Engineering
      Wu-han-shih, Hubei, China
  • 2008
    • Cardiff University
      • School of Engineering
      Cardiff, Wales, United Kingdom