• 沒有找到結果。

Conclusions and Further Researches

5.1 Conclusions

A novel OTPG for the auto-inspection of internal threads was proposed in this dissertation that provides a non-contact and an orientation-free internal thread inspection mechanism. The OTPG system captured a sequence of partial wall 2D images of the internal thread and converted them into a 2D unwrapped image. A preprocessing algorithm was designed to achieve repeatability when segmenting the inspected image. A DCT-based restoration technique was implemented to highlight defects such as scratches, collapses, and flaws in the directional texture image. The proposed OTPG can be used to detect both bulge-shaped scratch and cave-shape collapse or flaw.

47 5.2 Further Researches

The reconstructed 2D image loses the depth information of an internal thread pattern.

Some crucial features, such as the diameter and lead angle of the internal thread, are beyond the scope of this dissertation. The three-dimensional reconstruction of internal threads to improve automated optical measurement remains a subject for further research.

For the developed prototype OTPG, the inspection time includes image grabbing and image processing. The former takes about 10 minutes and the latter takes less than 6 seconds in inspecting an internal thread with diameter 15.3mm and length 20mm. The image registration time is the bottleneck of the OTPG approach. It is worth studying how to reduce the image registration time for further research.

48

References

[1] Hassel M (1994) A laser-based thread detection system. Sens Rev 14(3):18-19.

[2] Hassel M (1995) Laser-based feature detection system including internal thread detection.

IEEE/IAS Int Conf Ind Autom Control Emerg Technol 567-568. doi:

10.1109/IACET.1995.527621

[3] Gore M (1996) Internal thread inspection with capacitive sensors. Sens 12:48-49.

[4] Tu DW, Tao J, Qi S (1998) Computer-aided internal thread parameters testing. Proc SPIE 3558:234-238. doi:10.1117/12.318391

[5] Zhao Y, Li PS, Pu ZB (1999) MJ internal thread used for aerospace and its non-contact test method with a fiber optic sensor. Proc SPIE 3740:501-504. doi:10.1117/12.347727 [6] Zhao Y, Liao YB (2002) Single-mode fiber-based reflex sensor for internal surface

in-line measurement of small products. Sens Actuators A Phys 101(1-2):30-36.

doi:10.1016/S0924-4247(02)00143-7

[7] Zhao Y, Liao YB (2003) Research on measurement technology of internal MJ threads used for aerospace with a reflex fiber-optic sensor. Opt Eng 42(2):416-420.

doi:10.1117/1.1532742

[8] Field RH (2000) Detecting threads in machined holes: a look at eddy-current and other promising new probes. Manuf Eng 124(6):96, 98, 100-101.

[9] Wang XM, He J, He FY (2002) Leakage magnet detection system for inside screw steel pipes and flaw identification. Heavy Mach 6:18-21. (In Simplified Chinese)

[10] He FY, He J, Chen HD (2003) Inspection of the screw inside steel pipes and the testing system. Nondestruct Test 25(7):343-345, 368. (In Simplified Chinese)

[11] Lin JM, Lee TB, Lei H, Zheng Y (2005) The rotate and scan technique of eddy current test on screw and internal thread inspection. Nondestruct Insp 29(5):28-31. (In Simplified Chinese)

49

[12] Liu QM, Wang LS, Chen XW, Cui Z (2005) Non-damage measurement on internal taper thread of electrode. Opt Tech 31(2):309-314. (In Simplified Chinese)

[13] Lang WJ, George S (1988) Crampton and the origins of industrial endoscopy. Mater Eval 46: 1639-1642.

[14] Parenti R, Verrecchia P, Bosla G, Pignone E (1994) Industrialized real-time flame thermal thermal mapping system with off-line correction of spatial error. IEEE Int Conf Ind Electron Control Instrum 3:1977-1980. doi: 10.1109/IECON.1994.398122

[15] Tsushima T, Ishii A, Ochi Y, Masaoka N, Matsusue N (1997) Corrosion inspection of steel tube inner wall. IEEE/ASME Int Conf Adv Intell Mechatron 34. doi:

10.1109/AIM.1997.652892

[16] Boudjahi S, Ferreira A, Krupa A (2003) Modeling and vision-based control of a micro catheter head for teleopcrated in-pipe inspection. IEEE Int Conf Rob Autom 3:4282-4287. doi: 10.1109/ROBOT.2003.1242262

[17] Gu HT (2003) Industrial videoprobe’s application in Chinese civil aviation maintenance.

Test Equip Technol 6:56-57. (In Simplified Chinese)

[18] Biegelbauer G, Vincze M, Nohmayer H, Eberst C (2004) Sensor based robotics for fully automated inspection of cores at low volume high variant parts. IEEE Int Conf Rob Autom 5: 4852-4857. doi: 10.1109/ROBOT.2004.1302486

[19] Bondarev OY (2004) Application of industrial endoscope for the testing of a technical condition of a petroleum and gas industry objects. Kontrol’ Diagn 3:23-25.

[20] Ahn J, Schobeiri MT, Han JC, Moon HK (2006) Film cooling effectiveness on the leading edge region of a rotating turbine blade with two rows of film cooling holes using pressure sensitive paint. J Heat Transf 128(9):879-888. doi: 10.1115/1.2241945

[21] Ahn J, Schobeiri MT, Han JC, Moon HK (2007) Effect of rotation on leading edge region film cooling of a gas turbine blade with three rows of film cooling holes. Int J Heat Mass Transf 50(1-2):15-25. doi:10.1016/j.ijheatmasstransfer.2006.06.028

50

[22] Perng DB, Liu CP, Chen YC, Chou CC (2002) Advanced SMD PCB vision inspection machine development. 15th IPPR Conf Comput Vis Graph Image Process 311-317.

[23] Perng DB, Chou CC, Chen WY (2007) A novel vision system for CRT panel auto-inspection. J Chin Inst Ind Eng 24(5):341-350.

[24] Perng DB, Chen YC, Lee MK (2005) A novel AOI system for OLED panel inspection. J Phys Conf Ser 7th Int symp Meas Technol Intell Instru 13(1):353-356.

[25] Chen LC, Kuo CC (2008) Automatic TFT-LCD mura defect inspection using discrete cosine transform-based background filtering and ‘just noticeable difference’

quantification strategies. Meas Sci Technol 19(1):015507. doi:

10.1088/0957-0233/19/1/015507

[26] Perng DB, Chen YC (2009) An Advanced Auto-Inspection System for Micro-router Collapse. Mach Vision Appl (Accepted)

[27] Perng DB, Chou CC, Lee SM (2007) Design and development of a new machine vision wire bonding inspection system. Int J Adv Manuf Technol 34(3-4):323-334. doi:

10.1007/s00170-006-0611-6

[28] Lewis JP (1995) Fast normalized cross-correlation. Vis Interface 120-123.

[29] Fitch AJ, Kadyrov A, Christmas WJ, Kittler J (2005) Fast robust correlation. IEEE Trans Image Process 14(8):1063-1073. doi: 10.1109/TIP.2005.849767

[30] Kumar A (2008) Computer-vision-based fabric defect detection: a survey. IEEE Trans Ind Electron 55(1):348-363. doi: 10.1109/TIE.1930.896476

[31] Xie X (2008) A review of recent advances in surface defect detection using texture analysis techniques. Electron Lett Comput Vis Image Anal 7(3):1-22.

[32] Tsai DM, Hsieh CY (1999) Automated surface inspection for directional textures. Image Vis Comput 18(1):49-62. doi:10.1016/S0262-8856(99)00009-8

[33] Chen SH, Perng DB (2009) Automatic Surface Inspection for Directional Textures Using Discrete Cosine Transform. 2009 Chinese Conf Pattern Recognit.

51

[34] Tsai DM, Chiang CH (2003) Automatic band selection for wavelet reconstruction in the application of defect detection. Image Vis Comput 21:413-431.

doi:10.1016/S0262-8856(03)00003-9

[35] Lu CJ, Tsai DM (2005) Automatic defect inspection for LCDs using singular value decomposition. Int J Adv Manuf Technol 25:53-61. doi:10.1007/s00170-003-1832-6 [36] Perng DB, Chen SH (2009) Automatic surface inspection for directional textures using

principal component analysis. 20th Int Conf Prod Res.

[37] Lu CJ, Tsai DM (2008) Independent component analysis-based defect detection in patterned liquid crystal display surfaces. Image Vis Comput 26:955-970.

doi:10.1016/j.imavis.2007.10.007

[38] Newman TS, Jain AK (1995) Survey of automated visual inspection. Comput Vis Image Underst 61(2):231-262. doi: 10.1006/cviu.1995.1017

[39] Liu ST, Tsai WH (1989) Moment-preserving clustering. Pattern Recognit 22(4):433-447.

[40] Wang Z (1984) Fast algorithms for the discrete W transform and for the discrete fourier transform, IEEE Trans Acoust 32:803-816.