Fast drilling electrical discharge machining (EDM) is widely used in the manufacture of film cooling holes of turbine blades. However, due to the various hole orientations and severe electrode wear, it is relatively intricate to accurately and timely identify the critical moments such as breakout, hole completion in the drilling process, and adjust the machining strategy properly. Existing breakout detection and hole completion determination methods are not suitable for the high-efficiency and fully automatic production of film cooling holes, for they almost all depend on preset thresholds or training data and become less appropriate when machining condition changes. As the breakout and hole completion detection problems can be abstracted to an online stage identification problem, in this paper, a kurtosis-based stage identification (KBSI) method, which uses a novel normalized kurtosis to denote the recent changing trends of gap voltage signals, is developed for online stage identification. The identification accuracy and generalization ability of the KBSI method have been verified in various machining conditions. To improve the overall machining efficiency, the influence of servo control parameters on machining efficiency of each machining stage was analyzed experimentally, and a new stage-wise adaptive control strategy was then proposed to dynamically adjust the servo control parameters according to the online identification results. The performance of the new strategy is evaluated by drilling film cooling holes at different hole orientations. Experimental results show that with the new control strategy, machining efficiency and the machining quality can be significantly improved.
The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00434-w
Jian Wang
,
Xue-Cheng Xi
,
Ya-Ou Zhang
,
Fu-Chun Zhao
,
Wan-Sheng Zhao
. Stage identification and process optimization for fast drilling EDM of film cooling holes using KBSI method[J]. Advances in Manufacturing, 2023
, 11(3)
: 477
-491
.
DOI: 10.1007/s40436-022-00434-w
1. Wang J, Xi XC, Qin L et al (2021) Non-productive time optimization for 5-axis EDM drilling using HVNTS algorithm. Int J Prod Res 59(16):5068-5082
2. Wang J, Xi XC, Zhang YO et al (2021) Path optimization for multi-axis EDM drilling of combustor liner cooling holes using SCGA algorithm. Comput Ind Eng 157:107319. https://doi.org/10.1016/j.cie.2021.107319
3. Xia W, Zhang Y, Chen M et al (2020) Study on gap phenomena before and after the breakout event of fast electrical discharge machining drilling. J Manuf Sci Eng-Trans ASME 142(4):041004. https://doi.org/10.1115/1.4046249
4. Yamada S, Takawashi T, Sakakibara T (1984) Breakthrough detection means for electric discharge machining apparatus. Google Patents
5. Koshy P, Boroumand M, Ziada Y (2010) Breakout detection in fast hole electrical discharge machining. Int J Mach Tools Manuf 50(10):922-925
6. Xia W, Li Z, Zhang Y et al (2020) Breakout detection for fast EDM drilling by classification of machining state graphs. Int J Adv Manuf Technol 106(5):1645-1656
7. Zhang Y, Xia W, Li Z et al (2021) Completion detection and efficiency improvement for breakout stage of fast EDM drilling. Int J Adv Manuf Technol 114(5):1565-1574
8. Bellotti M, Qian J, Reynaerts D (2019) Breakthrough phenomena in drilling micro holes by EDM. Int J Mach Tools Manuf 146:103436. https://doi.org/10.1016/j.ijmachtools.2019.103436
9. Bellotti M, Qian J, Reynaerts D (2020) Self-tuning breakthrough detection for EDM drilling micro holes. J Manuf Process 57:630-640
10. Aich U (2018) Investigation for the presence of chaos in surface topography generated by EDM. Tribol Int 120:411-433
11. Zhao W, Chen M, Xia W et al (2020) Reconstructing CNC platform for EDM machines towards smart manufacturing. Procedia CIRP 95:161-177
12. Xia W, Li Z, Chen M et al (2020) Study on electrode vibration in the touch-down stage of fast electrical discharge machining drilling. Int J Adv Manuf Technol 109(7):2273-2283
13. Wang Z, Tong H, Li Y et al (2018) Dielectric flushing optimization of fast hole EDM drilling based on debris status analysis. Int J Adv Manuf Technol 97(5):2409-2417
14. Han F, Chen L, Yu D et al (2007) Basic study on pulse generator for micro-EDM. Int J Adv Manuf Technol 33(5):474-479
15. Wang Z, Zhou J, Wang J et al (2019) A novel fault diagnosis method of gearbox based on maximum kurtosis spectral entropy deconvolution. IEEE Access 7:29520-29532
16. Miao Y, Zhao M, Lin J et al (2017) Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings. Mech Syst Signal Proc 92:173-195
17. Dyer D, Stewart R (1978) Detection of rolling element bearing damage by statistical vibration analysis. J Mech Des 100(2):229-235
18. Xie B, Xiong Z, Wang Z et al (2020) Gamma spectrum denoising method based on improved wavelet threshold. Nucl Eng Technol 52(8):1771-1776
19. Lei J, Wu X, Zhou Z et al (2021) Sustainable mass production of blind multi-microgrooves by EDM with a long-laminated electrode. J Clean Prod 279:123492. https://doi.org/10.1016/j.jclepro.2020.123492