The property of high frequency in micro-EDM (electrical discharge machining) causes the discharge states to vary much faster than in conventional EDM, and discharge states of micro-EDM have the characteristics of nonstationarity, nonlinearity, and internal coupling, all of this makes it very difficult to carry out stable control. Thus empirical mode decomposition is adopted to conduct the prediction of the discharge states obtained through multisensor data fusion and fuzzy logic in micro-EDM. Combined with the autoregressive (AR) model identification and linear prediction, the mathematical model for EDM discharge state prediction using empirical mode decomposition is established and the corresponding prediction method is presented. Experiments demonstrate that the new prediction method with short identification data is highly accurate and operates quickly. Even using short model identification data, the accuracy of empirical mode decomposition prediction can stably reach a correlation of 74%, which satisfies statistical expectations. Additionally, the new process can also effectively eliminate the lag of conventional prediction methods to improve the efficiency of micro-EDM, and it provides a good basis to enhance the stability of the control system.
Skip Nav Destination
Article navigation
February 2010
Technical Briefs
A New Method for Discharge State Prediction of Micro-EDM Using Empirical Mode Decomposition
Zhenyuan Jia,
Zhenyuan Jia
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Search for other works by this author on:
Lingxuan Zhang,
Lingxuan Zhang
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Search for other works by this author on:
Fuji Wang,
Fuji Wang
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Search for other works by this author on:
Wei Liu
Wei Liu
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Search for other works by this author on:
Zhenyuan Jia
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Lingxuan Zhang
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Fuji Wang
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, China
Wei Liu
School of Mechanical Engineering,
Dalian University of Technology
, Dalian, Liaoning 116024, ChinaJ. Manuf. Sci. Eng. Feb 2010, 132(1): 014501 (6 pages)
Published Online: December 22, 2009
Article history
Received:
November 21, 2008
Revised:
October 25, 2009
Online:
December 22, 2009
Published:
December 22, 2009
Citation
Jia, Z., Zhang, L., Wang, F., and Liu, W. (December 22, 2009). "A New Method for Discharge State Prediction of Micro-EDM Using Empirical Mode Decomposition." ASME. J. Manuf. Sci. Eng. February 2010; 132(1): 014501. https://doi.org/10.1115/1.4000559
Download citation file:
Get Email Alerts
Cited By
On-Orbit Processing and Hardware Performance of Microgravity Hydrothermal Synthesis for Graphene Aerogel
J. Manuf. Sci. Eng (December 2024)
A Review on Metallic Drilling Burrs: Geometry, Formation, and Effect on the Mechanical Strength of Metallic Assemblies
J. Manuf. Sci. Eng (April 2025)
Related Articles
Data Rectification and Detection of Trend Shifts in Jet Engine Path Measurements Using Median Filters and Fuzzy Logic
J. Eng. Gas Turbines Power (October,2002)
Fuzzy Logic Control of Microhole Electrical Discharge Machining
J. Manuf. Sci. Eng (December,2008)
Servo Pneumatic Position Control Using Fuzzy PID Gain Scheduling
J. Dyn. Sys., Meas., Control (June,2004)
A Fuzzy Adaptive Simplex Search Optimization Algorithm
J. Mech. Des (June,2001)
Related Proceedings Papers
Related Chapters
Fuzzy Logic Voltage Flicker Estimation Using Hilbert Transform
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
Effectiveness of it Courses on the University Staffs Performance with Fuzzy Logic
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
A Fuzzy Logic Model for Improving Performance of Extended Vigilance in Automation Supervisory Task
Proceedings of the 2010 International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2010)