Chain discharging behavior induced by gas film expansion and its influence on the electrochemical discharge machining (ECDM) process

Liu, Guodong; Tong, Hao; Wu, Tianyi; Li, Yong; Luo, Yuge

doi:10.1007/s00170-022-10665-7

Cited by 10 publications

(2 citation statements)

References 22 publications

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“…Subsequently, Liu et al discovered the phenomenon of chain discharge caused by the expansion and morphology of the gas film for the first time. Chain discharge as a new phenomenon can help us to understand the mechanism and analyze the processing results of ECDM [ 20 ]. By observing the discharge effect on the gas film, Tang et al found that the shape of the gas film is influenced by the forces acting during the discharge process.…”

Section: Introductionmentioning

confidence: 99%

Study of Gas Film Characteristics in Electrochemical Discharge Machining and Their Effects on Discharge Energy Distribution

Liu

Adayi

2023

Micromachines

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Glass is a hard and brittle insulating material that is widely used in optics, biomedicine, and microelectromechanical systems. The electrochemical discharge process, which involves an effective microfabrication technology for insulating hard and brittle materials, can be used to perform effective microstructural processing on glass. The gas film is the most important medium in this process, and its quality is an important factor in the formation of good surface microstructures. This study focuses on the gas film properties and their influence on the discharge energy distribution. In this study, a complete factorial design of experiments (DOE) was used, with three factors and three levels of voltage, duty cycle, and frequency as the influencing factors and gas film thickness as the response for the experimental study, to obtain the best combination of process parameters that would result in the best gas film quality. In addition, experiments and simulations of microhole processing on two types of glass, quartz glass and K9 optical glass, were conducted for the first time to characterize the discharge energy distribution of the gas film based on the radial overcut, depth-to-diameter ratio, and roundness error, and to analyze the gas film characteristics and their effects on the discharge energy distribution. The experimental results demonstrated the optimal combination of process parameters, at a voltage of 50 V, a frequency of 20 kHz and a duty cycle of 80%, that achieved a better gas film quality and a more uniform discharge energy distribution. A thin and stable gas film with a thickness of 189 μm was obtained with the optimal combination of parameters, which was 149 μm less than the extreme combination of parameters (60 V, 25 kHz, 60%). These studies resulted in an 81 μm reduction in radial overcut, a roundness error reduced by 14, and a 49% increase in the depth–shallow ratio for a microhole machined on quartz glass.

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Section: Introductionmentioning

confidence: 99%

Study of Gas Film Characteristics in Electrochemical Discharge Machining and Their Effects on Discharge Energy Distribution

Liu

Adayi

2023

Micromachines

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“…Additionally, several endeavors have been undertaken to improve the performance of SACE machining, such as utilizing a mixed alkaline electrolyte (NaOH + KOH) [17], implementing Fig. 1 Schematic depiction of the SACE setup periodic bi-directional tool rotation [18] and inducing chain discharge [19]. Generally, SACE has demonstrated its potential as a remarkable candidate for rapidly prototyping various features with superior quality (aspect ratio of 11 and surface roughness of 300 nm [20]), coupled with an acceptable speed (feed rate of 200 µm/s [21]).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Characterization of Spark-Assisted Chemical Engraving (SACE) Process Using Time Series Classification

Sahebari,

Bassyouni,

Barari

et al. 2023

Preprint

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Spark-Assisted Chemical Engraving (SACE) requires precise control over key factors to overcome gas film instability and achieve reproducible optimal resolution and machining speed. This paper presents a substantial advancement in the SACE micromanufacturing technique by introducing a composite algorithm. This algorithm leverages deep learning and time series classification, employing a Temporal Convolutional Network (TCN) and a Long Short-Term Memory (LSTM) architecture for sequence-to-sequence intelligent classification. These classifiers are trained and optimized using Bayesian optimization, achieving impressive accuracies of 97.12% for TCN and 96.64% for LSTM. The algorithm utilizes TCN's superior performance to calculate derived parameters like gas film formation time, lifetime, mean discharge current and energy, and discharging frequency. Its versatility is demonstrated across various experimental conditions, showcasing its potential for rapid and accurate systematic studies. By highlighting the algorithm's applicability in real-time process control for SACE, this study establishes a foundation for future advancements in the field of glass micro manufacturing.

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Intelligent characterization of spark-assisted chemical engraving (SACE) process using time series classification

Seyedi Sahebari,

Bassyouni,

Barari

et al. 2023

Int J Adv Manuf Technol

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Chain discharging behavior induced by gas film expansion and its influence on the electrochemical discharge machining (ECDM) process

Cited by 10 publications

References 22 publications

Study of Gas Film Characteristics in Electrochemical Discharge Machining and Their Effects on Discharge Energy Distribution

Study of Gas Film Characteristics in Electrochemical Discharge Machining and Their Effects on Discharge Energy Distribution

Intelligent Characterization of Spark-Assisted Chemical Engraving (SACE) Process Using Time Series Classification

Intelligent characterization of spark-assisted chemical engraving (SACE) process using time series classification

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