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Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A012, June 21–25, 2021

Paper No: MSEC2021-62021

DOI: https://doi.org/10.1115/MSEC2021-62021

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Topics: Algorithms, Condition monitoring, Manufacturing, Signals

Proceedings Papers

Research on Flow and Heat Transfer Characteristics of Multiple Impinging Jets on a Moving Conveyor Belt

Rui Liu, Yu Sun, Jun Ni

Proc. ASME. IMECE2020, Volume 10: Fluids Engineering, V010T10A028, November 16–19, 2020

Paper No: IMECE2020-23272

DOI: https://doi.org/10.1115/IMECE2020-23272

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Topics: Conveyor belts, Flow (Dynamics), Heat transfer, Jets

Proceedings Papers

A Novel Edge Computing Based Architecture for Intelligent Tool Condition Monitoring

Rui Liu

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A015, September 3, 2020

Paper No: MSEC2020-8499

DOI: https://doi.org/10.1115/MSEC2020-8499

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Topics: Calibration, Condition monitoring, Manufacturing

Journal Articles

Algorithm for Accumulating Part Mating Gaps to Evaluate Solid and Fluid Performances

Jun Ni, Rui Liu, Yu Sun

J. Mech. Des. April 2021, 143(4): 043501.

Paper No: MD-20-1194

DOI: https://doi.org/10.1115/1.4047910

Published Online: October 28, 2020

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Topics: Algebra, Design, Fluids, Manufacturing, Turbines, Blades, Algorithms, Displacement

Proceedings Papers

Numerical Modeling of Water Impingement and Heat Transfer With Solid Slabs During Secondary Cooling in a Continuous Caster

Haibo Ma, Kaile Tang, Rui Liu, Michael Lowry, Armin Silaen, Chenn Zhou

Proc. ASME. IMECE2018, Volume 8A: Heat Transfer and Thermal Engineering, V08AT10A010, November 9–15, 2018

Paper No: IMECE2018-86691

DOI: https://doi.org/10.1115/IMECE2018-86691

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Topics: Computer simulation, Cooling, Heat transfer, Slabs, Water, Drops, Nozzles, Sprays, Heat, Collisions (Physics)

Proceedings Papers

An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance

Xuyue Yin, Xiumin Fan, Jiajie Wang, Rui Liu, Qiang Wang

Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A018, August 26–29, 2018

Paper No: DETC2018-85810

DOI: https://doi.org/10.1115/DETC2018-85810

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Topics: Manufacturing, Artificial neural networks, Neural network models

Proceedings Papers

Audio-Based Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

Achyuth Kothuru, Sai Prasad Nooka, Rui Liu

Proc. ASME. MSEC2018, Volume 4: Processes, V004T03A072, June 18–22, 2018

Paper No: MSEC2018-6680

DOI: https://doi.org/10.1115/MSEC2018-6680

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Topics: Artificial neural networks, Condition monitoring, Milling, Support vector machines, Wear, Machining, Cutting tools, Monitoring systems, Signals

Proceedings Papers

A Two-Layer Multi-Model Gas Path Fault Diagnosis Method

Yunpeng Cao, Yinghui He, Fang Yu, Jianwei Du, Shuying Li, Qingcai Yang, Rui Liu

Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A009, June 11–15, 2018

Paper No: GT2018-75368

DOI: https://doi.org/10.1115/GT2018-75368

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Topics: Fault diagnosis, Flaw detection, Gas turbines, Algorithms, Simulation, Artificial neural networks, Probability, Statistics as topic

Proceedings Papers

Gas Turbine Bearing Wear Monitoring Method Based on Magnetic Plug Inductance Sensor

Yunpeng Cao, Rui Liu, Jianwei Du, Fang Yu, Qingcai Yang, Yinghui He, Shuying Li

Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A002, June 11–15, 2018

Paper No: GT2018-75224

DOI: https://doi.org/10.1115/GT2018-75224

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Topics: Bearings, Gas turbines, Sensors, Wear, Lubricating oils, Signals, Wear testing, Artificial neural networks, Databases, Errors

Journal Articles

Audio-Based Tool Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

Achyuth Kothuru, Sai Prasad Nooka, Rui Liu

J. Manuf. Sci. Eng. November 2018, 140(11): 111006.

Paper No: MANU-18-1416

DOI: https://doi.org/10.1115/1.4040874

Published Online: August 3, 2018

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Topics: Artificial neural networks, Condition monitoring, Signals, Support vector machines, Wear, Cutting tools, Milling

Proceedings Papers

Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques

Achyuth Kothuru, Sai Prasad Nooka, Patricia Iglesias Victoria, Rui Liu

Proc. ASME. IDETC-CIE2017, Volume 10: 2017 ASME International Power Transmission and Gearing Conference, V010T11A030, August 6–9, 2017

Paper No: DETC2017-68067

DOI: https://doi.org/10.1115/DETC2017-68067

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Topics: Gears, Machine learning, Milling, Signals, Wear, Cutting, Cutting tools, Machining, Support vector machines, Algorithms

Proceedings Papers

Friction and Wear Properties of Halogen-Free and Halogen-Containing Ionic Liquids Used As Neat Lubricants, Lubricant Additives and Thin Lubricant Layers

Hong Guo, Rui Liu, Alfonso Fuentes-Aznar, Patricia Iglesias Victoria

Proc. ASME. IDETC-CIE2017, Volume 10: 2017 ASME International Power Transmission and Gearing Conference, V010T11A041, August 6–9, 2017

Paper No: DETC2017-67971

DOI: https://doi.org/10.1115/DETC2017-67971

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Topics: Friction, Lubricants, Wear, Mineral oil, Steel, Liquid metals, Lubrication

Proceedings Papers

Cutting Process Monitoring System Using Audible Sound Signals and Machine Learning Techniques: An Application to End Milling

Achyuth Kothuru, Sai Prasad Nooka, Rui Liu

Proc. ASME. MSEC2017, Volume 3: Manufacturing Equipment and Systems, V003T04A050, June 4–8, 2017

Paper No: MSEC2017-3069

DOI: https://doi.org/10.1115/MSEC2017-3069

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Topics: Cutting, Machine learning, Milling, Process monitoring, Signals, Wear, Algorithms, Cutting tools, Failure, Support vector machines

Proceedings Papers

Analysis and Control of the 1 st Order Interior Noise and Vibration Induced by Driveline Imbalance for 4WD Vehicle

Yuanfeng Xia, Jian Pang, Rui Liu, Wenjuan Li, Jianchun Xu

Proc. ASME. IMECE2016, Volume 4B: Dynamics, Vibration, and Control, V04BT05A063, November 11–17, 2016

Paper No: IMECE2016-65427

DOI: https://doi.org/10.1115/IMECE2016-65427

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Topics: Noise (Sound), Vehicles, Vibration, Separation (Technology), Acoustics, Cavities, Testing

Proceedings Papers

Effect of Cutting Conditions on Dimensional Accuracy and Surface Roughness in Traditional Milling of Steel

Brian Stringer, Rui Liu, Alfonso Fuentes Aznar, Patricia Iglesias

Proc. ASME. IMECE2016, Volume 2: Advanced Manufacturing, V002T02A004, November 11–17, 2016

Paper No: IMECE2016-66154

DOI: https://doi.org/10.1115/IMECE2016-66154

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Topics: Cutting, Milling, Steel, Surface roughness, Gears, Gear teeth, Blanks, Cutting tools, Errors, Manufacturing

Proceedings Papers

Stabilization of a Quadrotor With Uncertain Suspended Load Using Sliding Mode Control

Xu Zhou, Rui Liu, Jiucai Zhang, Xiaoli Zhang

Proc. ASME. IDETC-CIE2016, Volume 5A: 40th Mechanisms and Robotics Conference, V05AT07A048, August 21–24, 2016

Paper No: DETC2016-60060

DOI: https://doi.org/10.1115/DETC2016-60060

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Topics: Sliding mode control, Stress, Control equipment, Simulation results, Stability, Uncertainty, Robustness, Trajectories (Physics)

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Journal citation

NARROW

Experimental Investigation on Spray Evaporation and Dispersion Characteristics of Impinged Biodiesel-Butanol Blends

A Continuum Over Tube With Variable Stiffness for Transrectal NOTES

Combustion Performance Investigation of Aviation Kerosene (RP-3) on a Compression Ignition Diesel Engine Under Various Loads

A Flexible Similarity-Based Algorithm for Tool Condition Monitoring

A Flexible Similarity Based Algorithm for Tool Condition Monitoring

Research on Flow and Heat Transfer Characteristics of Multiple Impinging Jets on a Moving Conveyor Belt

A Novel Edge Computing Based Architecture for Intelligent Tool Condition Monitoring

Algorithm for Accumulating Part Mating Gaps to Evaluate Solid and Fluid Performances

Numerical Modeling of Water Impingement and Heat Transfer With Solid Slabs During Secondary Cooling in a Continuous Caster

An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance

Audio-Based Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

A Two-Layer Multi-Model Gas Path Fault Diagnosis Method

Gas Turbine Bearing Wear Monitoring Method Based on Magnetic Plug Inductance Sensor

Audio-Based Tool Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques

Friction and Wear Properties of Halogen-Free and Halogen-Containing Ionic Liquids Used As Neat Lubricants, Lubricant Additives and Thin Lubricant Layers

Cutting Process Monitoring System Using Audible Sound Signals and Machine Learning Techniques: An Application to End Milling

Analysis and Control of the 1 st Order Interior Noise and Vibration Induced by Driveline Imbalance for 4WD Vehicle

Effect of Cutting Conditions on Dimensional Accuracy and Surface Roughness in Traditional Milling of Steel

Stabilization of a Quadrotor With Uncertain Suspended Load Using Sliding Mode Control

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