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Prof. XiaoQi Chen
Deputy Director of Manufacturing Futures Research Institute and Professor in Department of Mechanical and Product Design Engineering, Swinburne University of Technology, John St, Hawthorn, VIC 3122, Australia

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0 Instrumentation
0 Robotics
0 Intelligent Manufacturing
0 autonomous systems
0 materials processing

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Journal article
Published: 27 July 2021 in Materials Science and Engineering: A
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Directed energy deposition (DED) of Inconel 718 is a promising process for the reconstruction of aerospace components, but a large number of Laves phases precipitated in inter-dendrites can impair the mechanical properties of the reconstructed parts. This paper puts forward a gradient laser power (GLP) deposition method to tailor the morphology and content of the Laves phase effectively, thereby enhancing the mechanical properties. The deposited Inconel 718 parts with the same volume as the Inconel 718 substrate were fabricated by different laser powers to simulate the practical thin-wall repair. An infrared camera was utilized to capture the thermal information during the DED process. The thermal-history-dependent microstructure, residual stress, microhardness and tensile properties were comprehensively investigated. The results indicate that the GLP method not only alleviates heat accumulation but also increases cooling rates and lateral heat dissipation. For GLP samples, the discrete and fine Laves phases tailored with a uniform distribution are featured by fine columnar dendrites with random growth direction, in sharp contrast to their long-chain interconnected configurations obtained by the conventional constant laser power (CLP) deposition method. Compared with CLP samples, GLP samples show compressive residual stress, high hardness and excellent ductility of elongation 30.09 % with comparable strength.

ACS Style

Luming Xu; Ze Chai; Huabin Chen; Xiaoqiang Zhang; Jibing Xie; Xiaoqi Chen. Tailoring Laves phase and mechanical properties of directed energy deposited Inconel 718 thin-wall via a gradient laser power method. Materials Science and Engineering: A 2021, 824, 141822 .

AMA Style

Luming Xu, Ze Chai, Huabin Chen, Xiaoqiang Zhang, Jibing Xie, Xiaoqi Chen. Tailoring Laves phase and mechanical properties of directed energy deposited Inconel 718 thin-wall via a gradient laser power method. Materials Science and Engineering: A. 2021; 824 ():141822.

Chicago/Turabian Style

Luming Xu; Ze Chai; Huabin Chen; Xiaoqiang Zhang; Jibing Xie; Xiaoqi Chen. 2021. "Tailoring Laves phase and mechanical properties of directed energy deposited Inconel 718 thin-wall via a gradient laser power method." Materials Science and Engineering: A 824, no. : 141822.

Journal article
Published: 26 May 2021 in Journal of Manufacturing Processes
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Modelling of grinding force and material removal rate (MRR) has been widely investigated for wheel grinding which often has a preset cutting depth, but is rather lacking for sand belt grinding. For robotic belt grinding where the normal force often remains constant, the cutting depth of individual grain varies as the abrasive grains wear with grinding time increasing. It is, therefore, a challenge to accurately predict the tangential force and resulted MRR, and subsequently control the finish profile. This paper develops grinding force model and material removal rate model based on single grain force for robotic belt grinding. It divides the whole grinding process into three stages: initial stage, steady stage and accelerated stage, based on the degree of grain wear, analyses the grinding force of rubbing, ploughing and cutting effects and MRR at each stage. By studying the distribution of grains and penetration depth of each grain, the grinding force and MRR are calculated. Experimental work on stainless steel 304 shows that the maximum errors of the tangential force prediction is 10.9% and that of MRR is 14.4%. The proposed models not only reveal the grinding mechanism but also predict the grinding force and MRR.

ACS Style

Lufeng Li; Xukai Ren; Hengjian Feng; Huabin Chen; Xiaoqi Chen. A novel material removal rate model based on single grain force for robotic belt grinding. Journal of Manufacturing Processes 2021, 68, 1 -12.

AMA Style

Lufeng Li, Xukai Ren, Hengjian Feng, Huabin Chen, Xiaoqi Chen. A novel material removal rate model based on single grain force for robotic belt grinding. Journal of Manufacturing Processes. 2021; 68 ():1-12.

Chicago/Turabian Style

Lufeng Li; Xukai Ren; Hengjian Feng; Huabin Chen; Xiaoqi Chen. 2021. "A novel material removal rate model based on single grain force for robotic belt grinding." Journal of Manufacturing Processes 68, no. : 1-12.

Article
Published: 24 May 2021 in International Journal of Dynamics and Control
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In practice, model-based fault diagnosis methods are essential to improve availability with reduced operating costs and good operational reliability of industrial systems. This is based firstly on the choice of the model identification method adapted to the system, depending on the complexity of the system and its interaction with its environment. Then, on the choice of an adequate diagnostic strategy for the generation of system failure indicators. In this work, the identification problem of the model variables of a double-shaft gas turbine is treated, to deal with the dynamics of model nonlinearities of this rotating machine. Hence, the equations which govern this turbine are carried out, using the local multi-models’ techniques with decoupled states, from the input/output measurements collected on the examined turbine. To best characterize their dynamic behavior in diverse operating areas. Subsequently, the resulting multi-model decoupled states are used to develop a fault diagnosis approach for this turbine. This makes it possible to generate symptoms of turbine failure from consistency tests between the measurements extracted on its real behavior, and the estimated signals which translate the reference behavior, given by the obtained multi-models. The obtained results in this work show the implementation efficiency of the proposed techniques of modeling and estimation of the examined decoupled turbine states, up to the phase of its implementation in the diagnostic strategy of the examined turbine based on the parity space approach.

ACS Style

Sidali Aissat; Ahmed Hafaifa; Abdelhamid Iratni; Mouloud Guemana; Xiaoqi Chen. Exploitation of multi-models identification with decoupled states in twin shaft gas turbine variables for its diagnosis based on parity space approach. International Journal of Dynamics and Control 2021, 1 -24.

AMA Style

Sidali Aissat, Ahmed Hafaifa, Abdelhamid Iratni, Mouloud Guemana, Xiaoqi Chen. Exploitation of multi-models identification with decoupled states in twin shaft gas turbine variables for its diagnosis based on parity space approach. International Journal of Dynamics and Control. 2021; ():1-24.

Chicago/Turabian Style

Sidali Aissat; Ahmed Hafaifa; Abdelhamid Iratni; Mouloud Guemana; Xiaoqi Chen. 2021. "Exploitation of multi-models identification with decoupled states in twin shaft gas turbine variables for its diagnosis based on parity space approach." International Journal of Dynamics and Control , no. : 1-24.

Original article
Published: 17 May 2021 in The International Journal of Advanced Manufacturing Technology
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Robotic grinding of welds on freeform surfaces poses an increasing challenge to automatic generation of grinding trajectory while conventional teaching-playback mode and off-line programming method are ineffective. This paper proposes a novel feature-guided trajectory generation method based on point cloud data to perform an efficient grinding process for welds on a freeform surface. The 3D contour of the workpiece was measured by a laser profile scanner. Parent curve of each scanning line was fitted by means of moving average filter, and then, the weld feature points were reliably extracted out of the scattered point cloud through two stages of feature recognition. To achieve the movement guidance of the manipulator, B-spline fitting method was conducted to generate a smooth 3D curve which was discretized into actual tool contact points by an optimized interpolation algorithm and computed the tool postures by cross multiply algorithm. By using robotic force control, the desired force was planned for every tool contact point in order to compensate the error of the processing path. Verification shows that the maximum root mean square root error of recognition of the proposed algorithm is less than 0.7 mm and the computational time is saved by 65.12% in comparison with the reverse engineering method.

ACS Style

Hengjian Feng; Xukai Ren; Lufeng Li; Xiaoqiang Zhang; Huabin Chen; Ze Chai; Xiaoqi Chen. A novel feature-guided trajectory generation method based on point cloud for robotic grinding of freeform welds. The International Journal of Advanced Manufacturing Technology 2021, 1 -19.

AMA Style

Hengjian Feng, Xukai Ren, Lufeng Li, Xiaoqiang Zhang, Huabin Chen, Ze Chai, Xiaoqi Chen. A novel feature-guided trajectory generation method based on point cloud for robotic grinding of freeform welds. The International Journal of Advanced Manufacturing Technology. 2021; ():1-19.

Chicago/Turabian Style

Hengjian Feng; Xukai Ren; Lufeng Li; Xiaoqiang Zhang; Huabin Chen; Ze Chai; Xiaoqi Chen. 2021. "A novel feature-guided trajectory generation method based on point cloud for robotic grinding of freeform welds." The International Journal of Advanced Manufacturing Technology , no. : 1-19.

Journal article
Published: 09 March 2021 in Journal of Manufacturing Processes
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Analyzing and modelling energy partition is of great significance to provide an in-depth understanding of the grinding process that is essentially dynamic. However, research on dynamic energy partition in belt grinding is rather scarce, especially from the perspective of a comprehensive energy evaluation. Here, we propose a novel energy partition model for belt grinding of Inconel 718, on basis of heat transfer analysis, finite element method and optimization algorithm. The model takes into account varying grinding force, grinding temperature, material removal rate and the heat accumulation in grains. Through an iterative approach, the dynamic energy entering the workpiece, belt, chips and ambient during grinding process can be obtained. Grinding temperature and dynamic energy partition calculation are validated. Results show that the maximum error of the calculated temperature is within 8.4 %. Further, effects of grinding parameters, grinding temperature and abrasive grains on belt grinding energy partition are analyzed and discussed in detail.

ACS Style

Xukai Ren; Xiaokang Huang; Hengjian Feng; Ze Chai; Yanbing He; Huabin Chen; Xiaoqi Chen. A novel energy partition model for belt grinding of Inconel 718. Journal of Manufacturing Processes 2021, 64, 1296 -1306.

AMA Style

Xukai Ren, Xiaokang Huang, Hengjian Feng, Ze Chai, Yanbing He, Huabin Chen, Xiaoqi Chen. A novel energy partition model for belt grinding of Inconel 718. Journal of Manufacturing Processes. 2021; 64 ():1296-1306.

Chicago/Turabian Style

Xukai Ren; Xiaokang Huang; Hengjian Feng; Ze Chai; Yanbing He; Huabin Chen; Xiaoqi Chen. 2021. "A novel energy partition model for belt grinding of Inconel 718." Journal of Manufacturing Processes 64, no. : 1296-1306.

Journal article
Published: 03 March 2021 in Journal of Manufacturing Systems
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Modern industry requires the development of new monitoring and diagnostic procedures, which enable the detection, localization, and isolation of faults. For sustainable solutions in terms of operational safety and availability, while bringing out zero accidents, zero downtime, and zero faults, for a trend acting on environmental issues. Towards this development, this work proposes solutions for the monitoring of gas turbines and their real-time implementation, in order to approximate and predict the degradation of the components of this system, by an approach of faults detection and isolation, based on an adaptive neural-fuzzy inference system. This will develop a reliable approach to maintain and monitor gas turbines, in case of failure or accident to prevent in real-time and makes it possible to achieve high power with efficiency and small footprint with High performance by operating this rotating machine. However, the application of the Adaptive Neuro-Fuzzy Inference System Observer-Based Approach, makes it possible to increase the life of the examined turbine and keep better reliability for their monitoring system and satisfy the techno-economic and environmental performance impacts. For the purpose of controlling failures and the occurrence of turbine system malfunctions, and avoiding their consequences on the safety and productivity of the installation.

ACS Style

Choayb Djeddi; Ahmed Hafaifa; Abdelhamid Iratni; Nadji Hadroug; Xiaoqi Chen. Robust diagnosis with high protection to gas turbine failures identification based on a fuzzy neuro inference monitoring approach. Journal of Manufacturing Systems 2021, 59, 190 -213.

AMA Style

Choayb Djeddi, Ahmed Hafaifa, Abdelhamid Iratni, Nadji Hadroug, Xiaoqi Chen. Robust diagnosis with high protection to gas turbine failures identification based on a fuzzy neuro inference monitoring approach. Journal of Manufacturing Systems. 2021; 59 ():190-213.

Chicago/Turabian Style

Choayb Djeddi; Ahmed Hafaifa; Abdelhamid Iratni; Nadji Hadroug; Xiaoqi Chen. 2021. "Robust diagnosis with high protection to gas turbine failures identification based on a fuzzy neuro inference monitoring approach." Journal of Manufacturing Systems 59, no. : 190-213.

Journal article
Published: 24 February 2021 in Journal of Materials Processing Technology
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Analyzing and modelling the dynamic energy partition is of great significance to revealing the mechanism of belt grinding and improving grinding quality. However, there is lack of comprehensive studies on energy partition in belt grinding, especially when the dynamic characteristics are under consideration. To fill this gap, this paper analyzed the grinding energy partition from the perspective of grinding effects and thermal aspects. Grinding effects are distinguished by combination of single grain scratch tests and force balance of one grain in view of dynamic and elastic contact conditions. Thermal aspects are obtained by a fusion method of finite element method (FEM) and optimization algorithm. Then, by utilizing the iterative approach, heat accumulating effect and temperature dependent mechanical properties of workpieces are taken into account either and the dynamic energy partition is calculated in a continuous grinding process. Validations on two workpieces (made by SUS304 and AA6061-T6) prove that the proposed dynamic energy partition calculating method is effective and the maximum error of qw is 17.2 %. The proposed method not only enhances the understanding of dynamic energy partition in robotic belt grinding, but also offers a new venue for studying abrasive belt grinding.

ACS Style

Xukai Ren; Xiaokang Huang; Ze Chai; Lufeng Li; Huabin Chen; Yanbing He; Xiaoqi Chen. A study of dynamic energy partition in belt grinding based on grinding effects and temperature dependent mechanical properties. Journal of Materials Processing Technology 2021, 294, 117112 .

AMA Style

Xukai Ren, Xiaokang Huang, Ze Chai, Lufeng Li, Huabin Chen, Yanbing He, Xiaoqi Chen. A study of dynamic energy partition in belt grinding based on grinding effects and temperature dependent mechanical properties. Journal of Materials Processing Technology. 2021; 294 ():117112.

Chicago/Turabian Style

Xukai Ren; Xiaokang Huang; Ze Chai; Lufeng Li; Huabin Chen; Yanbing He; Xiaoqi Chen. 2021. "A study of dynamic energy partition in belt grinding based on grinding effects and temperature dependent mechanical properties." Journal of Materials Processing Technology 294, no. : 117112.

Journal article
Published: 16 February 2021 in Actuators
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The ionic polymer metal composite (IPMC) actuator is a kind of soft actuator that can work for underwater applications. However, IPMC actuator control suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, for underwater applications, they are highly exposed to parametric uncertainties and external disturbances due to the inherent characteristics and working environment. Those factors significantly affect the positioning accuracy and reliability of IPMC actuators. Hence, feedback control techniques are vital in the control of IPMC actuators for suppressing the system uncertainty and external disturbance. In this paper, for the first time an adaptive full-order recursive terminal sliding-mode (AFORTSM) controller is proposed for the IPMC actuator to enhance the positioning accuracy and robustness against parametric uncertainties and external disturbances. The proposed controller incorporates an adaptive algorithm with terminal sliding mode method to release the need for any prerequisite bound of the disturbance. In addition, stability analysis proves that it can guarantee the tracking error to converge to zero in finite time in the presence of uncertainty and disturbance. Experiments are carried out on the IPMC actuator to verify the practical effectiveness of the AFORTSM controller in comparison with a conventional nonsingular terminal sliding mode (NTSM) controller in terms of smaller tracking error and faster disturbance rejection.

ACS Style

Romina Ekbatani; Ke Shao; Jasim Khawwaf; Hai Wang; Jinchuan Zheng; Xiaoqi Chen; Mostafa Nikzad. Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode. Actuators 2021, 10, 33 .

AMA Style

Romina Ekbatani, Ke Shao, Jasim Khawwaf, Hai Wang, Jinchuan Zheng, Xiaoqi Chen, Mostafa Nikzad. Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode. Actuators. 2021; 10 (2):33.

Chicago/Turabian Style

Romina Ekbatani; Ke Shao; Jasim Khawwaf; Hai Wang; Jinchuan Zheng; Xiaoqi Chen; Mostafa Nikzad. 2021. "Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode." Actuators 10, no. 2: 33.

Review
Published: 24 November 2020 in Applied Sciences
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With the development of Industry 4.0, additive manufacturing will be widely used to produce customized components. However, it is rather time-consuming and expensive to produce components with sound structure and good mechanical properties using additive manufacturing by a trial-and-error approach. To obtain optimal process conditions, numerous experiments are needed to optimize the process variables within given machines and processes. Digital twins (DT) are defined as a digital representation of a production system or service or just an active unique product characterized by certain properties or conditions. They are the potential solution to assist in overcoming many issues in additive manufacturing, in order to improve part quality and shorten the time to qualify products. The DT system could be very helpful to understand, analyze and improve the product, service system or production. However, the development of genuine DT is still impeded due to lots of factors, such as the lack of a thorough understanding of the DT concept, framework, and development methods. Moreover, the linkage between existing brownfield systems and their data are under development. This paper aims to summarize the current status and issues in DT for additive manufacturing, in order to provide more references for subsequent research on DT systems.

ACS Style

Li Zhang; Xiaoqi Chen; Wei Zhou; Taobo Cheng; Lijia Chen; Zhen Guo; Bing Han; Longxing Lu. Digital Twins for Additive Manufacturing: A State-of-the-Art Review. Applied Sciences 2020, 10, 8350 .

AMA Style

Li Zhang, Xiaoqi Chen, Wei Zhou, Taobo Cheng, Lijia Chen, Zhen Guo, Bing Han, Longxing Lu. Digital Twins for Additive Manufacturing: A State-of-the-Art Review. Applied Sciences. 2020; 10 (23):8350.

Chicago/Turabian Style

Li Zhang; Xiaoqi Chen; Wei Zhou; Taobo Cheng; Lijia Chen; Zhen Guo; Bing Han; Longxing Lu. 2020. "Digital Twins for Additive Manufacturing: A State-of-the-Art Review." Applied Sciences 10, no. 23: 8350.

Journal article
Published: 10 October 2020 in Materials & Design
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Directed energy deposition (DED) of Ni-based superalloys has wide applications in the fields of aviation, energy and power. However, for the non-weldable superalloys like Inconel 738, cracking frequently occurs during DED and cannot be thoroughly controlled up to now. We propose a novel method to prevent the cracking during Inconel 738 DED, in which a small amount of Inconel 718 is in-situ doped between the deposited layers of Inconel 738. The obtained layered-gradient-material is found to be free of both macro- and micro-cracks. The microstructure shows that doping Inconel 718 cannot interrupt the epitaxial growth of grains, but can modify the precipitation of γ′. In Inconel 718 layers, nano γ′ particles are intensively precipitated only in the inter-dendrites, while in Inconel 738 layers, they are precipitated in both the inter- and inner-dendrites. This modification on γ′ precipitation can effectively decrease the inner stress and alleviate the stress concentration at the grain boundaries, thus the cracking is prevented. The tensile tests, which were conducted at room temperature, 600 °C and 800 °C respectively, demonstrate that the composite deposited workpieces possess promising strength and plasticity. The proposed method has great potential to improve the printability of un-weldable superalloys in additive manufacturing.

ACS Style

Xiaoqiang Zhang; Ze Chai; Huabin Chen; Jijin Xu; Luming Xu; Hao Lu; Xiaoqi Chen. A novel method to prevent cracking in directed energy deposition of Inconel 738 by in-situ doping Inconel 718. Materials & Design 2020, 197, 109214 .

AMA Style

Xiaoqiang Zhang, Ze Chai, Huabin Chen, Jijin Xu, Luming Xu, Hao Lu, Xiaoqi Chen. A novel method to prevent cracking in directed energy deposition of Inconel 738 by in-situ doping Inconel 718. Materials & Design. 2020; 197 ():109214.

Chicago/Turabian Style

Xiaoqiang Zhang; Ze Chai; Huabin Chen; Jijin Xu; Luming Xu; Hao Lu; Xiaoqi Chen. 2020. "A novel method to prevent cracking in directed energy deposition of Inconel 738 by in-situ doping Inconel 718." Materials & Design 197, no. : 109214.

Journal article
Published: 24 July 2020 in Mathematics and Computers in Simulation
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The main purpose of the present work is to propose an effective tool which allows to ensure the protection and the safety measures against the instability phenomena in a gas turbine based on the modelling of its dynamic behaviour. In order to provide an efficient diagnostic strategy for this type of rotating machine, a supervision system based on the development of artificial neural network tools is proposed in this paper. Where, the dynamic nonlinear autoregressive approach with external exogenous input NARX is used for the identification of the studied system dynamics, to monitor the vibrational dynamics of the operating turbine. This leads to establishing a solution for the different ranges of rotational speed and ensuring dynamic stability through the vibration indicators, determined by the proposed neural network approach. Also, offer a normalized mean square error on the order of 3.8414e−3 for the high-pressure turbine, 1.29152e−1 for the gas control valve and 2.12090 e-4 for the air control valve. Furthermore, it permits the vibration monitoring and efficiently extracts the essentials of dynamic model behaviour, to effectively size the operating gas turbine system. The obtained results of the application of the proposed approach on the gas turbine system presented in this paper proves its ability for the detection and the management on real-time of the eventual failures caused mainly by intrinsic vibrations. On the other side, these results prove clearly the effectiveness of the use of the artificial neural networks as a very powerful calculation tools in the modelling of complex dynamic systems.

ACS Style

Mohamed Ben Rahmoune; Ahmed Hafaifa; Abdellah Kouzou; Xiaoqi Chen; Ahmed Chaibet. Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling. Mathematics and Computers in Simulation 2020, 179, 23 -47.

AMA Style

Mohamed Ben Rahmoune, Ahmed Hafaifa, Abdellah Kouzou, Xiaoqi Chen, Ahmed Chaibet. Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling. Mathematics and Computers in Simulation. 2020; 179 ():23-47.

Chicago/Turabian Style

Mohamed Ben Rahmoune; Ahmed Hafaifa; Abdellah Kouzou; Xiaoqi Chen; Ahmed Chaibet. 2020. "Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling." Mathematics and Computers in Simulation 179, no. : 23-47.

Journal article
Published: 18 July 2020 in Journal of Manufacturing Processes
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Robotic belt grinding is one of the most effective methods to process difficult-to-machine materials, such as Inconel 718. However, unpredictable heat generated in grinding area may destroy the surface quality of components. Computationally intensive numerical methods and inaccurate analytical methods cannot reliably obtain the heat input in grinding processes online. To this end, we propose a novel method based on multi-sensor and machine learning techniques to achieve online dynamic heat input monitoring. Firstly, comparison of the dynamic and static heat input is performed for illustrating the necessity of online heat input monitoring. Secondly, through associating the grinding signals (sound and force) with the heat input and developed feature selection method, a BADS-LSSVM (Bayesian adaptive direct research-least squares support vector machine) based model is proposed to predict the heat input. Test results show that the proposed method has a mean accuracy of no less than 96.7 %, a computed temperature error of ±6 °C in a complete grinding pass; and takes about 0.6 s for each calculation. With this new method, the real-time heat input monitoring is achieved and the subsequent thermal control of robotic belt grinding can be further conducted in future.

ACS Style

Xukai Ren; Ze Chai; Jijin Xu; Xiaoqiang Zhang; Yanbing He; Huabin Chen; Xiaoqi Chen. A new method to achieve dynamic heat input monitoring in robotic belt grinding of Inconel 718. Journal of Manufacturing Processes 2020, 57, 575 -588.

AMA Style

Xukai Ren, Ze Chai, Jijin Xu, Xiaoqiang Zhang, Yanbing He, Huabin Chen, Xiaoqi Chen. A new method to achieve dynamic heat input monitoring in robotic belt grinding of Inconel 718. Journal of Manufacturing Processes. 2020; 57 ():575-588.

Chicago/Turabian Style

Xukai Ren; Ze Chai; Jijin Xu; Xiaoqiang Zhang; Yanbing He; Huabin Chen; Xiaoqi Chen. 2020. "A new method to achieve dynamic heat input monitoring in robotic belt grinding of Inconel 718." Journal of Manufacturing Processes 57, no. : 575-588.

Original article
Published: 29 June 2020 in The International Journal of Advanced Manufacturing Technology
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Large tensile residual stress is detrimental to the structural integrity of welded structures. As a result, it is very important to understand the residual formation during the welding process. In this paper, a new non-contact welding residual stress measurement technique based on digital image correlation (DIC) is proposed as a way to investigate residual stress formation. To investigate the stress evolution of the welded plate, we conduct a series of experiments by using this new method. High-temperature full-field strain obtained from DIC was computed by incremental theory to acquire stress increment. Stress evolution and residual stress were obtained by superimposing the stress increment. Hole-drilling residual stress measurements for verification were also implemented. The maximum difference, which was 37 MPa between the two methods demonstrated that this new technique was able to characterize the full-field welding residual stress during the welding process.

ACS Style

Huabin Chen; Yulin Song; Xiaoqi Chen; Xinghua Yu; Shanben Chen. In situ studies of full-field residual stress mapping of SS304 stainless steel welds using DIC. The International Journal of Advanced Manufacturing Technology 2020, 109, 1 -11.

AMA Style

Huabin Chen, Yulin Song, Xiaoqi Chen, Xinghua Yu, Shanben Chen. In situ studies of full-field residual stress mapping of SS304 stainless steel welds using DIC. The International Journal of Advanced Manufacturing Technology. 2020; 109 (1-2):1-11.

Chicago/Turabian Style

Huabin Chen; Yulin Song; Xiaoqi Chen; Xinghua Yu; Shanben Chen. 2020. "In situ studies of full-field residual stress mapping of SS304 stainless steel welds using DIC." The International Journal of Advanced Manufacturing Technology 109, no. 1-2: 1-11.

Original article
Published: 20 February 2020 in The International Journal of Advanced Manufacturing Technology
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High-performance components with complex geometries make it difficult to determine the position and orientation of grinding tool. In this work, a fast and accurate robotic grinding path planning method is proposed for automatic removal of irregular weldments on a free form surface. The surface of workpiece is digitalized by 3D profile scanner and represented by point cloud data. Statistic filter, weighted least square regression and differences of normal vectors are used for point cloud pre-processing and segmentation. All segments are then modelled by B-spline surfaces to obtain the parent surface. A new superposition method is proposed to create a computer-aided design (CAD) model of the actual workpiece by adding the weld seam to the parent surface. The CAD model is then imported into an off-line simulation system to generate and execute grinding path. With the superposition method, the heights and widths of weld seam are extracted by analysing the difference between point cloud data and the reconstructed parent surface in order to determine the feed rate and size of grinding tool. Experimental results show that the proposed superposition method has the maximum absolute percentage error 5.3% and 41% saving in computation time in comparison with the conventional reverse engineering method.

ACS Style

Xiangfei Wang; Xiaoqiang Zhang; Xukai Ren; Lufeng Li; Hengjian Feng; Yanbing He; Huabin Chen; Xiaoqi Chen. Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning. The International Journal of Advanced Manufacturing Technology 2020, 107, 827 -841.

AMA Style

Xiangfei Wang, Xiaoqiang Zhang, Xukai Ren, Lufeng Li, Hengjian Feng, Yanbing He, Huabin Chen, Xiaoqi Chen. Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning. The International Journal of Advanced Manufacturing Technology. 2020; 107 (1-2):827-841.

Chicago/Turabian Style

Xiangfei Wang; Xiaoqiang Zhang; Xukai Ren; Lufeng Li; Hengjian Feng; Yanbing He; Huabin Chen; Xiaoqi Chen. 2020. "Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning." The International Journal of Advanced Manufacturing Technology 107, no. 1-2: 827-841.

Journal article
Published: 19 November 2019 in BMC Biomedical Engineering
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Background Hybrid exoskeletons are a recent development which combine Functional Electrical Stimulation with actuators to improve both the mental and physical rehabilitation of stroke patients. Hybrid exoskeletons have been shown capable of reducing the weight of the actuator and improving movement precision compared to Functional Electrical Stimulation alone. However little attention has been given towards the ability of hybrid exoskeletons to reduce and manage Functional Electrical Stimulation induced fatigue or towards adapting to user ability. This work details the construction and testing of a novel assist-as-need upper-extremity hybrid exoskeleton which uses model-based Functional Electrical Stimulation control to delay Functional Electrical Stimulation induced muscle fatigue. The hybrid control is compared with Functional Electrical Stimulation only control on a healthy subject. Results The hybrid system produced 24° less average angle error and 13.2° less Root Mean Square Error, than Functional Electrical Stimulation on its own and showed a reduction in Functional Electrical Stimulation induced fatigue. Conclusion As far as the authors are aware, this is the study which provides evidence of the advantages of hybrid exoskeletons compared to use of Functional Electrical Stimulation on its own with regards to the delay of Functional Electrical Stimulation induced muscle fatigue.

ACS Style

Ashley Stewart; Christopher Pretty; Xiaoqi Chen. A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation. BMC Biomedical Engineering 2019, 1, 1 -17.

AMA Style

Ashley Stewart, Christopher Pretty, Xiaoqi Chen. A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation. BMC Biomedical Engineering. 2019; 1 (1):1-17.

Chicago/Turabian Style

Ashley Stewart; Christopher Pretty; Xiaoqi Chen. 2019. "A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation." BMC Biomedical Engineering 1, no. 1: 1-17.

Journal article
Published: 01 November 2019 in Journal of Mechanical Design
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This paper introduces the equations of motion of modular 2D snake robots moving in vertical plane employing Series Elastic Actuators (SEAs). The kinematics of such 2D modular snake robot is presented in an efficient matrix form and Euler–Lagrange equations are constructed to model the robot. Moreover, using a spring-damper contact model, external contact forces, necessary for modeling pedal wave motion (undulation in the vertical plane) are taken into account, which unlike existing methods can be used to model the effect of multiple contact points. Using such a contact model, pedal wave motion of the robot is simulated and the torque signal measured by the elastic element from the simulation and experimentation are used to show the validity of the model. Moreover, pedal wave locomotion of such robot on uneven terrain is also modeled and an adaptive controller based on torque feedback in gait parameter's space with optimized control gain is proposed. The simulation and experimentation results showed the efficacy of the proposed controller as the robot successfully climbed over a stair-type obstacle without any prior knowledge about its location with at least 24.8% higher speed compared with non-adaptive motion.

ACS Style

Mohammadali Javaheri Koopaee; Christopher Pretty; Koen Classens; Xiaoqi Chen. Dynamical Modeling and Control of Modular Snake Robots With Series Elastic Actuators for Pedal Wave Locomotion on Uneven Terrain. Journal of Mechanical Design 2019, 142, 1 -46.

AMA Style

Mohammadali Javaheri Koopaee, Christopher Pretty, Koen Classens, Xiaoqi Chen. Dynamical Modeling and Control of Modular Snake Robots With Series Elastic Actuators for Pedal Wave Locomotion on Uneven Terrain. Journal of Mechanical Design. 2019; 142 (3):1-46.

Chicago/Turabian Style

Mohammadali Javaheri Koopaee; Christopher Pretty; Koen Classens; Xiaoqi Chen. 2019. "Dynamical Modeling and Control of Modular Snake Robots With Series Elastic Actuators for Pedal Wave Locomotion on Uneven Terrain." Journal of Mechanical Design 142, no. 3: 1-46.

Conference paper
Published: 24 August 2019 in Transactions on Intelligent Welding Manufacturing
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Development of automated machining robots has gained momentum with many well-known processes realizing automation to improve quality and increase efficiency. However, grinding process is difficult to automate. High temperature at the contact between the grinding wheel and the workpiece is the source of thermal deformation and phase transformations which can lead to thermal damage and affect surface integrity. This study aims to achieve a better understanding of the thermal behaviour of the grinding process in order to develop an automated grinding robotic system. We studied the thermal behaviour of Inconel 718 workpiece during the grinding process. Different models have been established previously to characterize the heat generation and dispersion at the interface between grinding wheel and workpiece. The Rowe model is used to calculate the heat escaping from the workpiece, by convection, and convection with the grinding wheel in order to obtain the heat remaining in the workpiece. Once the heat source intensity is calculated, Jaeger’s model for moving heat sources is used to calculate the evolution of the temperature along the length of a bar being ground and along the depth in steady state. A numerical model is created using ABAQUS to take into account non-linearity such as the temperature dependence of the parameters and complex boundary conditions. An experiment is carried out on an Inconel 718 bar to compare with the analytical and numerical results. The results show that the boundary condition and the temperature dependence properties of Inconel 718 cannot be neglected. The temperature profiles obtained by the numerical model, which includes the boundary condition and temperature dependence properties of material, are more consistent with the experimental results.

ACS Style

Xukai Ren; Baptiste Soulard; Junwei Wang; Yanling Xu; Xiaoqi Chen. Thermal Analysis of Belt Grinding Process of Nickel-Based Superalloy Inconel 718. Transactions on Intelligent Welding Manufacturing 2019, 57 -74.

AMA Style

Xukai Ren, Baptiste Soulard, Junwei Wang, Yanling Xu, Xiaoqi Chen. Thermal Analysis of Belt Grinding Process of Nickel-Based Superalloy Inconel 718. Transactions on Intelligent Welding Manufacturing. 2019; ():57-74.

Chicago/Turabian Style

Xukai Ren; Baptiste Soulard; Junwei Wang; Yanling Xu; Xiaoqi Chen. 2019. "Thermal Analysis of Belt Grinding Process of Nickel-Based Superalloy Inconel 718." Transactions on Intelligent Welding Manufacturing , no. : 57-74.

Journal article
Published: 07 August 2019 in Materials & Design
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Laser Melting Deposition (LMD) of Inconel 738 (IN738) superalloy is a promising process for the remanufacturing of gas turbines and aerospace engines, but the cracking has not been thoroughly understood and controlled. This paper conducts a comprehensive study on the cracking behavior by using optical microscope (OM), scanning electron microscopy (SEM), energy dispersion spectrum (EDS), electron backscatter diffraction (EBSD), X-ray diffraction (XRD) and differential scanning calorimetry (DSC). The results indicate that liquation cracking which follows the penetration mechanism is the major origin to those cracks. Whereas, at the propagation stage, ductility-dip cracking (DDC) is an important supplement to liquation cracking, especially at the triple junction points of grain boundaries (GBs) or the bottom of already formed liquation cracks. The cracks are very sensitive to GB morphology, the long-straight GBs which result from higher heat input or unidirectional scanning strategy are very vulnerable to cracking. Moreover, GB oxidation always plays an important role in accelerating crack propagation, the local protection from the cladding head is not enough for the LMD of IN738. For these factors, the test specimens which are bidirectionally deposited in an Argon (Ar) chamber with lower heat input achieve better tensile strengthen reaching 1093 to 1116 MPa.

ACS Style

Xiaoqiang Zhang; Huabin Chen; Luming Xu; Jijin Xu; Xukai Ren; Xiaoqi Chen. Cracking mechanism and susceptibility of laser melting deposited Inconel 738 superalloy. Materials & Design 2019, 183, 108105 .

AMA Style

Xiaoqiang Zhang, Huabin Chen, Luming Xu, Jijin Xu, Xukai Ren, Xiaoqi Chen. Cracking mechanism and susceptibility of laser melting deposited Inconel 738 superalloy. Materials & Design. 2019; 183 ():108105.

Chicago/Turabian Style

Xiaoqiang Zhang; Huabin Chen; Luming Xu; Jijin Xu; Xukai Ren; Xiaoqi Chen. 2019. "Cracking mechanism and susceptibility of laser melting deposited Inconel 738 superalloy." Materials & Design 183, no. : 108105.

Original article
Published: 05 August 2019 in The International Journal of Advanced Manufacturing Technology
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High-performance component manufacturing has increasing needs of robotic grinding process that can achieve accurate material removal. This article proposes a novel material removal model for robotic belt grinding of Inconel 718 based on acoustic sensing and machine learning. The sound signal is collected online by an audio sensor during the grinding process. A novel method to identify the idle running period and eliminate noise is developed using discrete wavelet decomposition (DWD) and fast Fourier transformation (FFT). Statistical features are extracted from each clean acoustic signal segment to better represent and quantify grinding process. A new k-fold eXtreme Gradient Boosting (k-fold-XGBoost) algorithm after training and optimization is integrated into the material removal (MR) model. The test results indicate that the values forecasted by the model are consistent with the measured values. The mean absolute percentage error (MAPE) of material removal evaluated by the model is 4.373%, which shows a better performance than the reported results which are in the range of 6.4 to 8.72%. In comparison with other prediction models, such as optimally pruned extreme learning machine and random forest and support vector regression, k-fold-XGBoost model shows superior results for the same datasets. It can be concluded that the proposed method based on acoustic signal and the ensemble learning model is effective in predicting the material removal despite the complicated grinding environment.

ACS Style

KaiYuan Gao; Huabin Chen; Xiaoqiang Zhang; Xukai Ren; Junqi Chen; Xiaoqi Chen. A novel material removal prediction method based on acoustic sensing and ensemble XGBoost learning algorithm for robotic belt grinding of Inconel 718. The International Journal of Advanced Manufacturing Technology 2019, 105, 217 -232.

AMA Style

KaiYuan Gao, Huabin Chen, Xiaoqiang Zhang, Xukai Ren, Junqi Chen, Xiaoqi Chen. A novel material removal prediction method based on acoustic sensing and ensemble XGBoost learning algorithm for robotic belt grinding of Inconel 718. The International Journal of Advanced Manufacturing Technology. 2019; 105 (1-4):217-232.

Chicago/Turabian Style

KaiYuan Gao; Huabin Chen; Xiaoqiang Zhang; Xukai Ren; Junqi Chen; Xiaoqi Chen. 2019. "A novel material removal prediction method based on acoustic sensing and ensemble XGBoost learning algorithm for robotic belt grinding of Inconel 718." The International Journal of Advanced Manufacturing Technology 105, no. 1-4: 217-232.

Article
Published: 30 July 2019 in Journal of Bionic Engineering
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This paper presents the design and manufacture process of a wheel-less, modular snake robot with series elastic actuators to reliably measure motor torque signal and investigate the effectiveness of active stiffness control for achieving adaptive snake-like locomotion. A polyurethane based elastic element to be attached between the motor and the links at each joint was designed and manufactured using water jet cutter, which makes the final design easier to develop and more cost-effective, compared to existing snake robots with torque measurement capabilities. The reliability of such torque measurement mechanism was examined using simulated dynamical model of pedal wave motion, which proves the efficacy of the design. A distributed control system was also designed, which with the help of an admittance controller, enables active control of the joint stiffness to achieve adaptive snake robot pedal wave locomotion to climb over obstacles, which unlike existing methods does not require prior information about the location of the obstacle. The effectiveness of the proposed controller in comparison to open-loop control strategy was verified by the number of experiments. The results show the capability of the robot to successfully climb over obstacles with the height of more than 55% of the diameter of the snake robot modules.

ACS Style

Mohammadali Javaheri Koopaee; Sander Bal; Christopher Pretty; Xiaoqi Chen. Design and Development of a Wheel-less Snake Robot with Active Stiffness Control for Adaptive Pedal Wave Locomotion. Journal of Bionic Engineering 2019, 16, 593 -607.

AMA Style

Mohammadali Javaheri Koopaee, Sander Bal, Christopher Pretty, Xiaoqi Chen. Design and Development of a Wheel-less Snake Robot with Active Stiffness Control for Adaptive Pedal Wave Locomotion. Journal of Bionic Engineering. 2019; 16 (4):593-607.

Chicago/Turabian Style

Mohammadali Javaheri Koopaee; Sander Bal; Christopher Pretty; Xiaoqi Chen. 2019. "Design and Development of a Wheel-less Snake Robot with Active Stiffness Control for Adaptive Pedal Wave Locomotion." Journal of Bionic Engineering 16, no. 4: 593-607.