journal article·2026-05Open access

Study of laser-electrochemical machining of deep small holes based on lensed fiber coupling

Tong Li, Yufeng Wang, Wenming Jiang, Yong Yang, Wenwu Zhang

Abstract

Laser-electrochemical hybrid machining (LECM) combines the high materials removal rate of laser processing with the superior surface quality of electrochemical machining (ECM), offering a potent solution for the low-damage, high-efficiency drilling of difficult-to-cut materials. To overcome the limitations of unstable laser coupling and constrained optical field modulation in conventional LECM, this study proposes a lensed fiber-based LECM process. By employing coaxial lensed fiber for laser transmission and in-situ focusing, the laser energy is spatially confined to the central zone for primary material removal, while the peripheral region is simultaneously processed by ECM to ensure high-precision, low-damage feature of the small hole. Optical simulations reveal that the lensed fiber reduces the output spot width by 54.2% while increasing the maximum laser intensity by 307.2%. The effects of laser power, feed rate, and voltage on machining accuracy and material removal rate(MRR) were investigated. The processing parameters were optimized through an orthogonal experimental design, and the optimal parameters were determined to be a voltage of 22 V, a feeding rate of 1.6 mm/min, and a laser power of 5 W. Finally, a small hole with a diameter of 1.4 mm and a depth of 10 mm was successfully fabricated free of recast layer or micro-cracks, with a surface roughness of Ra 1.3 μm. Furthermore, laser coupling with tool electrode via lensed fiber focusing was also proposed for LECM, and a laser coupling efficiency of larger than 70% was achieved.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Laser Material Processing Techniques · Advanced Machining and Optimization Techniques · Advanced Surface Polishing Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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