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砾综邹
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1 65 Journal o Technology, Vol. 30, o. 1, pp (2015) 1 1 1, * 關鍵詞 : HE DIAGOSIS OF GRIDIG STATE THROUGH THE COMBIATIO OF TIME-FREQUECY AALYSIS AD STATISTICAL PROCESS COTROL Yeon-Pun Chang 1 Jun-Jie Fang 1 Yuan Kang 1, * Kai-Ming Chang 1 Chun-Chieh Wang 2 1 Department o Mechanical Engineering Chung Yuan Christian University Chung Li City, Taiwan 320, R.O.C. 2 Mechanical and Systems Research Laboratories Industrial Technology Research Institute Hsinchu City, Taiwan 300, R.O.C. Key Words: surace grinder, statistical process control, time-requency analysis, mirror-polished. ABSTRACT This study mainly explored the relationship between process vibration signals o surace grinders and the quality o inished processing parts. The processing conditions aecting the quality o workpieces include: grinding wheels, cutting luids, eed, and so on. Four types o quality states are usually seen in workpieces that undergo mirror polishing, include normal, scratches, chatter lines, and burns. In order to detect the quality o the inished workpieces, the surace grinder spender s process vibration signals and the time-requency were extracted, which underwent time-requency statistical characteristics analysis. The statistical characteristics parameters * yk@cycu.edu.tw Corresponding author: Yuan Kang, yk@cycu.edu.tw

2 66 o the process vibration signals that represent the quality o the workpieces were extracted. Then, the statistical characteristics parameters were added to the statistical process control in order to monitor the quality o the workpieces through the use o control diagrams, thereby quickly tracing the time attributable causes that took place and adopt corresponding methods to return to the normal state. Tönsho, Friemuth Becker [1] Bi [2] [3] Dennis [4] Al-Badour, Cheded Sunar [5] Mataragasa [6] Card [7] Paulk [8] LabVIEW x(t) x i=x1, x 2,..., x 2 1. (mean value) 1 = xi (1) i=1 2. (Standard Deviation) 1 = x 2 ( i ) (2) i=1 3. (Variance) 1 = x 2 ( i ) (3) i=1 4. (autocorrelation) -1 1 = xx (4) τ i i-τ -1 i= 1 = 1

3 67 1. (t) x(t) x(t) t STFT STFT t, ω = x( t) ( t t) e -jwt dt (5) - (t) t SPE t, ω = x( t) ( t t) e -jwt dt (6) - z(k) k STFT(t, ) 2 2π -jnk L STFTZ ( m, n ) = z( k) ( k m) e (7) k=- m n L (t)(7) 2 SPE ( m, n ) = STFT ( m, n ) (8) Z z Hz 1 Hz n n = (9) n m = (10) n un un s n =n (11) n= ( n1) m (12) (11) (12) un UCL LCL CL UCL ( ) 列 2 1 UCL CL LCL 異 1 UCL LCL CL CL = (13) n

4 68 1 UCL = (14) LCL = (15) (14) (15) UCL LCL Hz Hz 1~32 Hz 33~64 Hz (a) 3(b) 3(c) 3(d) I 9174 I cdaq 9234 LabVIEW WA60K8V 3(e) 3() AISI 1020 X Y 3 Z 5 m X 120 mm 14.4 m/minz 5 my 55 mm 0.5 mm 110 3

5 Y 110 Z (a) (b) (c) (d) 7 2. SPC 7

6 () (1) (2) (3) (4) () (1) (2) 6 27 (3) 2 3 (4) (5) ()

7 71 9 ()

8 72 x() t L m n n m s un n UCL CL LCL 1. Tönsho, H. K., Friemuth, T., and Becker, J. C., Process Monitoring in Grinding, Journal o Manuacturing Technology, Vol. 51, o. 2, pp (2002). 2. Bi, G., Guo, Y., Lin, J., Han, W., Zheng, M., and Chen, X., Principles o An In-process Monitoring System or Precision Grinding Machine, 2nd Intemational Conerence on Mechanic Automation and Control Engineering, Hohhot, China, pp (2011) (2004) 4. Dennis, G., Theory o communications, Journal o the Institution o Electrical Engineers, Vol. 93, o. 4, pp (1946). 5. Al-Badour, F., Cheded, L., and Sunar, M., on-stationary Vibration Signal Analysis o Rotating Machinery via Time-Frequency and Wavelet Techniques, th International Conerence on Inormation Sciences Signal Processing and their Applications (ISSPA), Kuala Lumpur, Malaysia, pp (2010). 6. Mataragasa, M., Drosinosa, E. H., Tsolab, E., Zoiopoulosb, P. E., Integrating Statistical Process control to Monitor and Improve Carcasses Quality in a Poultry Slaughterhouse Implementing a HACCP System, Food Control, Vol. 28, o. 2, pp (2012). 7. Card, D., Statistical Process Control or Sotware?, IEEE Sotware, Vol 11, o. 3, pp (1994). 8. Paulk, M. C., Applying SPC to the personal sotware process, Proceedings o the 10th International Conerence on Sotware Quality, ew Orleans, LA, Vol. 10, pp (2000)

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