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Prof. Zhanqun Shi
School of Mechanical engineering, Hebei University of Technology, 300401, Tianjin-China

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Conference paper
Published: 16 May 2021 in Proceedings of the 9th IFToMM International Conference on Rotor Dynamics
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The dynamic responses of hydrodynamically lubricated surfaces have attracted many researchers for the sake of improving both the lubrication performances and online lubrication monitoring. To gain insightful understandings of dynamic interactions in a fluid lubricated joint that are the fundamentals of many key mechanical components such as bearings and seals in the engine, a series of engine lubricants were tested in a cone-plate rheometer and the corresponding acoustic emission (AE) signals are acquired to monitor the dynamic interactions of tribofilm shearing with surface asperities. The observations show that the AE measurements are sensitive to the change of lubrication conditions, specifically shearing rates. A greater shear rate can excite a wider frequency bandwidth and stronger AE signals. This AE response with respect to the engine lubricants samples can be explained by the dynamic fluid-asperity shearing model. These findings provide important guidelines for analysing the online measured AE signals from complex machines.

ACS Style

Jiaojiao Ma; Zhanqun Shi; Hao Zhang; Fengshou Gu; Andrew D. Ball. An Experiment Study of Acoustic Emission Generated by Dynamic Fluid Asperity Shearing. Proceedings of the 9th IFToMM International Conference on Rotor Dynamics 2021, 14 -22.

AMA Style

Jiaojiao Ma, Zhanqun Shi, Hao Zhang, Fengshou Gu, Andrew D. Ball. An Experiment Study of Acoustic Emission Generated by Dynamic Fluid Asperity Shearing. Proceedings of the 9th IFToMM International Conference on Rotor Dynamics. 2021; ():14-22.

Chicago/Turabian Style

Jiaojiao Ma; Zhanqun Shi; Hao Zhang; Fengshou Gu; Andrew D. Ball. 2021. "An Experiment Study of Acoustic Emission Generated by Dynamic Fluid Asperity Shearing." Proceedings of the 9th IFToMM International Conference on Rotor Dynamics , no. : 14-22.

Journal article
Published: 07 January 2021 in Measurement
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In the hydrodynamic lubricated journal bearing system, the surface roughness and angular misalignment are two critical factors that affect bearing’s performance. In this paper, the coupled effects of different non-Gaussian properties and misalignments are investigated on the performance of journal bearings. Christensen’s stochastic model is extended by improving the probability density function of random roughness heights, which incorporates the Gram-Charlier expansion including skewness and kurtosis. In comparison with a Gaussian surface, the non-Gaussian rough surface has more significant influence on the bearing static performance. The negative skewness and large kurtosis increase the load capacity and decrease the friction coefficient. According to the simulations and experiments, non-Gaussian properties have more impact on the performance than misalignment when the journal bearing is operated in hydrodynamic lubrication regime based on different pressure distributions and vibration responses. These novel findings provide the basis for monitoring the conditions of hydrodynamic journal bearings.

ACS Style

Jiaojiao Ma; Chao Fu; Hao Zhang; Fulei Chu; Zhanqun Shi; Fengshou Gu; Andrew D. Ball. Modelling non-Gaussian surfaces and misalignment for condition monitoring of journal bearings. Measurement 2021, 174, 108983 .

AMA Style

Jiaojiao Ma, Chao Fu, Hao Zhang, Fulei Chu, Zhanqun Shi, Fengshou Gu, Andrew D. Ball. Modelling non-Gaussian surfaces and misalignment for condition monitoring of journal bearings. Measurement. 2021; 174 ():108983.

Chicago/Turabian Style

Jiaojiao Ma; Chao Fu; Hao Zhang; Fulei Chu; Zhanqun Shi; Fengshou Gu; Andrew D. Ball. 2021. "Modelling non-Gaussian surfaces and misalignment for condition monitoring of journal bearings." Measurement 174, no. : 108983.

Journal article
Published: 01 December 2020 in Advances in Science, Technology and Engineering Systems Journal
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ACS Style

Abubakar Umar; Zhanqun Shi; Lin Zheng; Alhadi Khlil; Zulfiqar Ibrahim Bibi Farouk. Parameter Estimation for Industrial Robot Manipulators Using an Improved Particle Swarm Optimization Algorithm with Gaussian Mutation and Archived Elite Learning. Advances in Science, Technology and Engineering Systems Journal 2020, 5, 1436 -1457.

AMA Style

Abubakar Umar, Zhanqun Shi, Lin Zheng, Alhadi Khlil, Zulfiqar Ibrahim Bibi Farouk. Parameter Estimation for Industrial Robot Manipulators Using an Improved Particle Swarm Optimization Algorithm with Gaussian Mutation and Archived Elite Learning. Advances in Science, Technology and Engineering Systems Journal. 2020; 5 (6):1436-1457.

Chicago/Turabian Style

Abubakar Umar; Zhanqun Shi; Lin Zheng; Alhadi Khlil; Zulfiqar Ibrahim Bibi Farouk. 2020. "Parameter Estimation for Industrial Robot Manipulators Using an Improved Particle Swarm Optimization Algorithm with Gaussian Mutation and Archived Elite Learning." Advances in Science, Technology and Engineering Systems Journal 5, no. 6: 1436-1457.

Journal article
Published: 24 April 2020 in Sensors
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The vibration of a planetary gearbox (PG) is complex and mutually modulated, which makes the weak features of incipient fault difficult to detect. To target this problem, a novel method, based on an adaptive order bispectrum slice (AOBS) and the fault characteristics energy ratio (FCER), is proposed. The order bispectrum (OB) method has shown its effectiveness in the feature extraction of bearings and fixed-shaft gearboxes. However, the effectiveness of the PG still needs to be explored. The FCER is developed to sum up the fault information, which is scattered by mutual modulation. In this method, the raw vibration signal is firstly converted to that in the angle domain. Secondly, the characteristic slice of AOBS is extracted. Different from the conventional OB method, the AOBS is extracted by searching for a characteristic carrier frequency adaptively in the sensitive range of signal coupling. Finally, the FCER is summed up and calculated from the fault features that were dispersed in the characteristic slice. Experimental data was processed, using both the AOBS-FCER method, and the method that combines order spectrum analysis with sideband energy ratio (OSA-SER), respectively. Results indicated that the new method is effective in incipient fault feature extraction, compared with the methods of OB and OSA-SER.

ACS Style

Zhaoyang Shen; Zhanqun Shi; Dong Zhen; Hao Zhang; Fengshou Gu. Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis. Sensors 2020, 20, 2433 .

AMA Style

Zhaoyang Shen, Zhanqun Shi, Dong Zhen, Hao Zhang, Fengshou Gu. Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis. Sensors. 2020; 20 (8):2433.

Chicago/Turabian Style

Zhaoyang Shen; Zhanqun Shi; Dong Zhen; Hao Zhang; Fengshou Gu. 2020. "Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis." Sensors 20, no. 8: 2433.

Journal article
Published: 22 January 2020 in Mathematics
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Metaheuristics are incapable of analyzing robot problems without being enhanced, modified, or hybridized. Enhanced metaheuristics reported in other works of literature are problem-specific and often not suitable for analyzing other robot configurations. The parameters of standard particle swarm optimization (SPSO) were shown to be incapable of resolving robot optimization problems. A novel algorithm for robot kinematic analysis with enhanced parameters is hereby presented. The algorithm is capable of analyzing all the known robot configurations. This was achieved by studying the convergence behavior of PSO under various robot configurations, with a view of determining new PSO parameters for robot analysis and a suitable adaptive technique for parameter identification. Most of the parameters tested stagnated in the vicinity of strong local minimizers. A few parameters escaped stagnation but were incapable of finding the global minimum solution, this is undesirable because accuracy is an important criterion for robot analysis and control. The algorithm was trained to identify stagnating solutions. The algorithm proposed herein was found to compete favorably with other algorithms reported in the literature. There is a great potential of further expanding the findings herein for dynamic parameter identification.

ACS Style

Abubakar Umar; Zhanqun Shi; Alhadi Khlil; Zulfiqar I. B. Farouk. Developing a New Robust Swarm-Based Algorithm for Robot Analysis. Mathematics 2020, 8, 158 .

AMA Style

Abubakar Umar, Zhanqun Shi, Alhadi Khlil, Zulfiqar I. B. Farouk. Developing a New Robust Swarm-Based Algorithm for Robot Analysis. Mathematics. 2020; 8 (2):158.

Chicago/Turabian Style

Abubakar Umar; Zhanqun Shi; Alhadi Khlil; Zulfiqar I. B. Farouk. 2020. "Developing a New Robust Swarm-Based Algorithm for Robot Analysis." Mathematics 8, no. 2: 158.

Journal article
Published: 20 January 2020 in Sensors
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The dynamic coefficients identification of journal bearings is essential for instability analysis of rotation machinery. Aiming at the measured displacement of a single location, an improvement method associated with the Kalman filter is proposed to estimate the bearing dynamic coefficients. Firstly, a finite element model of the flexible rotor-bearing system was established and then modified by the modal test. Secondly, the model-based identification procedure was derived, in which the displacements of the shaft at bearings locations were estimated by the Kalman filter algorithm to identify the dynamic coefficients. Finally, considering the effect of the different process noise covariance, the corresponding numerical simulations were carried out to validate the preliminary accuracy. Furthermore, experimental tests were conducted to confirm the practicality, where the real stiffness and damping were comprehensively identified under the different operating conditions. The results show that the proposed method is not only highly accurate, but also stable under different measured locations. Compared with the conventional method, this study presents a more than high practicality approach to identify dynamic coefficients, including under the resonance condition. With high efficiency, it can be extended to predict the dynamic behaviour of rotor-bearing systems.

ACS Style

Yang Kang; Zhanqun Shi; Hao Zhang; Dong Zhen; Fengshou Gu. A Novel Method for the Dynamic Coefficients Identification of Journal Bearings Using Kalman Filter. Sensors 2020, 20, 565 .

AMA Style

Yang Kang, Zhanqun Shi, Hao Zhang, Dong Zhen, Fengshou Gu. A Novel Method for the Dynamic Coefficients Identification of Journal Bearings Using Kalman Filter. Sensors. 2020; 20 (2):565.

Chicago/Turabian Style

Yang Kang; Zhanqun Shi; Hao Zhang; Dong Zhen; Fengshou Gu. 2020. "A Novel Method for the Dynamic Coefficients Identification of Journal Bearings Using Kalman Filter." Sensors 20, no. 2: 565.

Conference paper
Published: 22 August 2019 in Journal of Physics: Conference Series
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In present years, the simulation technique has been extensively used in manufacturing processes, solving complex problems with least time, effort and cost. This paper presented a virtual simulation of automatic quality measurement system for tapered roller bearing to aid the decision-making processes, observe system operation processes and provide an initial design for constructing processes using 3D modeling process and Python programming language, the proposed system was intended to check the tapered roller bearing dimensions and to achieve the prescribed goals, the 3D model was built, the virtual environment has been created and the motion control process was applied in 3DAutomate software.

ACS Style

Alhadi Khlil; B Ma; Z Shi. Virtual Simulation of Automatic Quality Measurement System for Tapered Roller Bearing Based on 3D Automate Software. Journal of Physics: Conference Series 2019, 1284, 012022 .

AMA Style

Alhadi Khlil, B Ma, Z Shi. Virtual Simulation of Automatic Quality Measurement System for Tapered Roller Bearing Based on 3D Automate Software. Journal of Physics: Conference Series. 2019; 1284 (1):012022.

Chicago/Turabian Style

Alhadi Khlil; B Ma; Z Shi. 2019. "Virtual Simulation of Automatic Quality Measurement System for Tapered Roller Bearing Based on 3D Automate Software." Journal of Physics: Conference Series 1284, no. 1: 012022.

Journal article
Published: 01 September 2018 in Sensors
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The planetary gearbox is at the heart of most rotating machinery. The premature failure and subsequent downtime of a planetary gearbox not only seriously affects the reliability and safety of the entire rotating machinery but also results in severe accidents and economic losses in industrial applications. It is an important and challenging task to accurately detect failures in a planetary gearbox at an early stage to ensure the safety and reliability of the mechanical transmission system. In this paper, a novel method based on wavelet packet energy (WPE) and modulation signal bispectrum (MSB) analysis is proposed for planetary gearbox early fault diagnostics. First, the vibration signal is decomposed into different time-frequency subspaces using wavelet packet decomposition (WPD). The WPE is calculated in each time-frequency subspace. Secondly, the relatively high energy vectors are selected from a WPE matrix to obtain a reconstructed signal. The reconstructed signal is then subjected to MSB analysis to obtain the fault characteristic frequency for fault diagnosis of the planetary gearbox. The validity of the proposed method is carried out through analyzing the vibration signals of the test planetary gearbox in two fault cases. One fault is a chipped sun gear tooth and the other is an inner-race fault in the planet gear bearing. The results show that the proposed method is feasible and effective for early fault diagnosis in planetary gearboxes.

ACS Style

Junchao Guo; Zhanqun Shi; Haiyang Li; Dong Zhen; Fengshou Gu; Andrew D. Ball. Early Fault Diagnosis for Planetary Gearbox Based Wavelet Packet Energy and Modulation Signal Bispectrum Analysis. Sensors 2018, 18, 2908 .

AMA Style

Junchao Guo, Zhanqun Shi, Haiyang Li, Dong Zhen, Fengshou Gu, Andrew D. Ball. Early Fault Diagnosis for Planetary Gearbox Based Wavelet Packet Energy and Modulation Signal Bispectrum Analysis. Sensors. 2018; 18 (9):2908.

Chicago/Turabian Style

Junchao Guo; Zhanqun Shi; Haiyang Li; Dong Zhen; Fengshou Gu; Andrew D. Ball. 2018. "Early Fault Diagnosis for Planetary Gearbox Based Wavelet Packet Energy and Modulation Signal Bispectrum Analysis." Sensors 18, no. 9: 2908.

Journal article
Published: 02 April 2018 in Sensors
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Small cracks are common defects in steel and often lead to catastrophic accidents in industrial applications. Various nondestructive testing methods have been investigated for crack detection; however, most current methods focus on qualitative crack identification and image processing. In this study, eddy current pulsed thermography (ECPT) was applied for quantitative crack detection based on derivative analysis of temperature variation. The effects of the incentive parameters on the temperature variation were analyzed in the simulation study. The crack profile and position are identified in the thermal image based on the Canny edge detection algorithm. Then, one or more trajectories are determined through the crack profile in order to determine the crack boundary through its temperature distribution. The slope curve along the trajectory is obtained. Finally, quantitative analysis of the crack sizes was performed by analyzing the features of the slope curves. The experimental verification showed that the crack sizes could be quantitatively detected with errors of less than 1%. Therefore, the proposed ECPT method was demonstrated to be a feasible and effective nondestructive approach for quantitative crack detection.

ACS Style

Zhanqun Shi; Xiaoyu Xu; Jiaojiao Ma; Dong Zhen; Hao Zhang. Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography. Sensors 2018, 18, 1070 .

AMA Style

Zhanqun Shi, Xiaoyu Xu, Jiaojiao Ma, Dong Zhen, Hao Zhang. Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography. Sensors. 2018; 18 (4):1070.

Chicago/Turabian Style

Zhanqun Shi; Xiaoyu Xu; Jiaojiao Ma; Dong Zhen; Hao Zhang. 2018. "Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography." Sensors 18, no. 4: 1070.

Journal article
Published: 06 July 2015 in Combustion Science and Technology
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ACS Style

Dong Zhen; Zhongyue Song; Zhanqun Shi; Fengshou Gu; Andrew Ball. Combustion Noise Analysis for Combustion and Fuels Diagnosis of a CI Diesel Engine Operating with Biodiesels. Combustion Science and Technology 2015, 187, 1974 -1992.

AMA Style

Dong Zhen, Zhongyue Song, Zhanqun Shi, Fengshou Gu, Andrew Ball. Combustion Noise Analysis for Combustion and Fuels Diagnosis of a CI Diesel Engine Operating with Biodiesels. Combustion Science and Technology. 2015; 187 (12):1974-1992.

Chicago/Turabian Style

Dong Zhen; Zhongyue Song; Zhanqun Shi; Fengshou Gu; Andrew Ball. 2015. "Combustion Noise Analysis for Combustion and Fuels Diagnosis of a CI Diesel Engine Operating with Biodiesels." Combustion Science and Technology 187, no. 12: 1974-1992.

Conference paper
Published: 19 July 2011 in Journal of Physics: Conference Series
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ACS Style

Hao Zhang; Zhanqun Shi; Fengshou Gu; Andrew Ball. Modelling of Outer and Inner Film Oil Pressure for Floating Ring Bearing Clearance in Turbochargers. Journal of Physics: Conference Series 2011, 305, 1 .

AMA Style

Hao Zhang, Zhanqun Shi, Fengshou Gu, Andrew Ball. Modelling of Outer and Inner Film Oil Pressure for Floating Ring Bearing Clearance in Turbochargers. Journal of Physics: Conference Series. 2011; 305 ():1.

Chicago/Turabian Style

Hao Zhang; Zhanqun Shi; Fengshou Gu; Andrew Ball. 2011. "Modelling of Outer and Inner Film Oil Pressure for Floating Ring Bearing Clearance in Turbochargers." Journal of Physics: Conference Series 305, no. : 1.

Conference paper
Published: 01 January 2006 in Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering
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Lubrication condition strongly influences the behaviour and operational life of a rolling element bearing. This paper presented an experimental investigation of rolling element bearings with no lubricant and with grease-lubricant containing contaminants using the acoustic emission (AE) technique. High frequency sampling and data streaming technology were applied in the measurement of AE, instead of traditionally measured AE parameters such as the counts, events, and peak amplitude of the signal etc. By processing the AE signals with frequency domain analysis technology, the no lubricant and containing contaminants conditions can be clearly discriminated. This result proved that the frequency domain AE signal processing technique is a suitable method for monitoring the lubrication condition in rolling element bearings.

ACS Style

Yibo Edward Fan; Zhanqun Shi; Georgina Harris; Fengshou Gu; Andrew Ball. Monitoring the Lubrication Condition of Rolling Element Bearings Using the Acoustic Emission Technique. Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering 2006, 2006, 843 -848.

AMA Style

Yibo Edward Fan, Zhanqun Shi, Georgina Harris, Fengshou Gu, Andrew Ball. Monitoring the Lubrication Condition of Rolling Element Bearings Using the Acoustic Emission Technique. Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering. 2006; 2006 ():843-848.

Chicago/Turabian Style

Yibo Edward Fan; Zhanqun Shi; Georgina Harris; Fengshou Gu; Andrew Ball. 2006. "Monitoring the Lubrication Condition of Rolling Element Bearings Using the Acoustic Emission Technique." Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering 2006, no. : 843-848.

Conference paper
Published: 01 January 2006 in Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering
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In this paper, the model-based approach is introduced into rotation machinery fault detection to achieve an automatic feature extraction. The paper starts with a brief review of the model-based approach, including model development, residual generation and fault detection and diagnosis. The applicability of this approach to rotation machinery is then considered. In order to overcome difficulties arising from phase shift and random measurements, the statistical performance of the vibration of rotation machinery is analysed in both time and frequency domains. A consistence model is developed using stochastic process theory. After model validation, the model-based approach is implemented in AC motor fault detection. The residual is generated by comparing the new measurement and the model prediction, by both subtraction and division. Fault detection results prove that the model-based approach is applicable to fault feature extraction for rotation machinery in the frequency domain.

ACS Style

Zhanqun Shi; Andrew Higson; Lin Zheng; Fengshou Gu; Andrew Ball. Automatic Fault Detection Using a Model-Based Approach in the Frequency Domain. Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering 2006, 849 -855.

AMA Style

Zhanqun Shi, Andrew Higson, Lin Zheng, Fengshou Gu, Andrew Ball. Automatic Fault Detection Using a Model-Based Approach in the Frequency Domain. Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering. 2006; ():849-855.

Chicago/Turabian Style

Zhanqun Shi; Andrew Higson; Lin Zheng; Fengshou Gu; Andrew Ball. 2006. "Automatic Fault Detection Using a Model-Based Approach in the Frequency Domain." Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering , no. : 849-855.

Conference paper
Published: 01 January 2004 in Volume 1
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This paper aims to combine neural network modelling with model-based fault detection. An accurate and robust model is critical in model-based fault detection. However, the development of such a model is the most difficult task especially when a non-linear system is involved. The problem comes not only from the lack of concerned information about model parameters, but also from the inevitable linearization. In order to solve this problem, neural networks are introduced in this paper. Instead of using conventional neural network modelling, the neural network is only used to approximate the non-linear part of the system, leaving the linear part to be represented by a mathematical model. This new scheme of integration between neural network and mathematical model (NNMM) allows the compensation of the error from conventional modelling methods. Simultaneously, it keeps the residual signatures physically interpretable.

ACS Style

Zhanqun Shi; Yibo Fan; Fengshou Gu; Abdul-Hannan Ali; Andrew Ball. Neural Network Modelling Applied for Model-Based Fault Detection. Volume 1 2004, 149 -155.

AMA Style

Zhanqun Shi, Yibo Fan, Fengshou Gu, Abdul-Hannan Ali, Andrew Ball. Neural Network Modelling Applied for Model-Based Fault Detection. Volume 1. 2004; ():149-155.

Chicago/Turabian Style

Zhanqun Shi; Yibo Fan; Fengshou Gu; Abdul-Hannan Ali; Andrew Ball. 2004. "Neural Network Modelling Applied for Model-Based Fault Detection." Volume 1 , no. : 149-155.

Conference paper
Published: 01 January 2004 in Volume 1
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The integration of control and monitoring systems often restricts more advanced monitoring algorithms to be used because of the limitation of hardware resource. This paper proposed a remote on-line model-based monitoring scheme, in which the monitoring and the control are implemented in different stations but synchronised through a Fieldbus network. Moreover, the synchronism period is adjustable so that it allows implementation of various monitoring tasks of different monitoring accuracy. This approach is demonstrated by applying it to a mechatronic control system. The implementation details are presented and the benefits of the approach are highlighted.

ACS Style

Zhanqun Shi; Fengshou Gu; Robert Pietruszkiewicz; Andrew Ball. Remote Model-Based Condition Monitoring Applied to a Mechatronic Control System. Volume 1 2004, 157 -162.

AMA Style

Zhanqun Shi, Fengshou Gu, Robert Pietruszkiewicz, Andrew Ball. Remote Model-Based Condition Monitoring Applied to a Mechatronic Control System. Volume 1. 2004; ():157-162.

Chicago/Turabian Style

Zhanqun Shi; Fengshou Gu; Robert Pietruszkiewicz; Andrew Ball. 2004. "Remote Model-Based Condition Monitoring Applied to a Mechatronic Control System." Volume 1 , no. : 157-162.