臺灣博碩士論文加值系統

本研究目的在於發展一滾珠螺桿進給系統之診斷技術基於滾珠螺桿與軸承之振動訊號。其區分為兩部分，在第一部分中，採用主成份分析法(Principal component analysis, PCA)於自動化監測滾珠螺桿進給系統預壓之改變，用以量化呈現滾珠螺桿進給系統之預壓變化，並評估此法的可行性及有效性。
滾珠螺桿部分中提出四種與預壓最具相關之量化振動指標，分別為實際球通階次、球通振動量、階次譜分散度、球通振動變異數。透過簡易貼置於螺帽上之加速規量測振動訊號，並經由角速度馮卡曼濾波器(Angular velocity Vold-Kalman filtering order tracking, AV VKF-OT)計算出此四指標，可藉由四指標確實地實現及大幅改善監測螺桿預壓變化之準效性；此外，提出將預壓相關四指標應用於PCA，用以預估滾珠螺桿剩餘壽命，其準確率由實驗結果得知，預測誤差低於15%。
第二部分中，發展一振動量測訊號應用於自組織映射圖(Self-organizing map, SOM)之滾珠軸承診斷系統，數個由包絡譜提取之振動指標，搭配費雪分數之排名法挑選有效鑑別軸承健康狀態之指標以使用於系統中。由實驗結果可知，此系統診斷與監測健康狀態之結果相當準確，其準確率達90%以上。

The purpose of this research is to develop a diagnosis system for ball screw feed drive systems based on monitoring the vibration signal on bearings and ball screw nut. This systems was divided into two parts. In the first part, a novel method in monitoring automatically the preload degradation for a ball screw feed drive system based on principal component analysis(PCA) is presented and its performance is assessed. Four feature from an vibration order spectrum, the actual ball pass order (ABPO), the vibration RMS amplitude at ABPO, the variance of vibration at ABPO and the dispersion of order spectra are proposed to quantify the difference in characteristics between ball screws with and without preloads. By simply attaching an accelerometer on the ball screw nut of a ball screw feed drive system in operation, these four parameters are calculated by using angular velocity Vold-Kalman filtering order tracking (AV VKF-OT). With these four parameters, the prediction accuracy in monitoring the ball screw preload degradation is much improved and can be realized practically. Furthermore, a screw degradation indicator based on the four parameters and PCA is proposed to estimate the ball screw remaining life. Experimental results show that the ball screw remaining life can be estimated with an error less than 15%.
In the second part, a bearing diagnosis system using vibration measurements and self-organizing map (SOM) is developed. Several features extracted from the vibration envelope spectra are assessed and ranked using Fisher score in distinguishing a healthy bearing form the faulty one. Experimental results show that with this system the bearing can be monitored and the diagnosis is accurate.

目 錄 I
圖目錄 III
表目錄 VII
第一章 緒論 1
1-1 前言 1
1-2 研究動機與目的 1
1-3 文獻回顧 2
1-3-1 滾珠螺桿預壓力偵測 2
1-3-2 軸承故障診斷 4
1-3-3 文獻回顧總結 5
1-4 研究流程與方法 6
第二章 滾珠螺桿預壓力偵測與壽命預估技術 9
2-1 滾珠螺桿球通頻率與預壓力之關係 9
2-2 角速度馮卡曼濾波器階次追蹤法 13
2-2-1 結構與資料方程式 13
2-2-2 最小平方法 14
2-3 主成份分析法之應用 20
2-4 滾珠螺桿預壓即時監測與壽命預估技術 25
2-4-1 預壓力即時監測技術 25
2-4-2 滾珠螺桿壽命估測方法 28
第三章 滾珠軸承健康診斷 33
3-1 包絡譜分析之解析訊號 33
3-2 滾珠軸承故障特徵 36
3-3 特徵擷取與費雪分數排名法之應用 38
3-4 自組織映射圖之應用 43
3-4-1 SOM之演算法 44
3-4-2 軸承診斷機制 52
第四章 進給系統之健康監測 55
4-1 滾珠螺桿壽命預估技術之應用 55
4-1-1 螺桿門檻建立與預估判斷機制 57
4-1-2 結果與討論 59
4-2 滾珠軸承健康診斷 64
4-2-1 資料擷取系統與實驗平台 64
4-2-2 實驗流程與實驗設計 69
4-2-3 結果與討論 76
第五章 結論與未來展望 97
5-1 研究結論 97
5-2 未來研究方向 99
參考文獻 101

[1] M.C. Lin, B. Ravani and S. Velinsky, “Kinematic of the Ball Screw Mechanism,” ASME Journal of Mechanical Design, Vol. 116, pp. 849-855, 1994.
[2] M. C. Lin, B. Ravani and S. Velinsky, “Design of the Ball Screw Mechanism for Optimal Efficiency,” ASME Journal of Mechanical Design, Vol. 116, pp. 856-861, 1994.
[3] 魏進忠，單螺帽雙圈滾珠螺桿在預壓及潤滑作用條件下運動機制與機械性能的理論分析及實驗印證，國立成功大學機械工程研究所博士論文，2003。
[4] C. C. Wei and J. F. Lin, “Kinematic Analysis of the Ball Screw Mechanism Considering Variable Contact Angles and Elastic Deformations,” ASME Journal of Mechanical Design, Vol. 125, pp. 717-733, 2003.
[5] 蘇栢賢，滾珠導螺桿振動噪音之研究，國立清華大學動力機械工程研究所碩士論文，2005。
[6] 李起榮，滾珠螺桿進給系統預壓偵測技術之研發，國立中正大學機械工程研究所碩士論文，2013。
[7] 許夫瀚，具預壓之滾珠螺桿其振動特性之分析，國立中正大學機械工程研究所碩士論文，2014。
[8] 李孟軒，滾珠螺桿進給系統振動特性之分析，國立中正大學機械工程研究所碩士論文，2015。
[9] J. W. Cooley and J. W. Tukey, “An Algorithm for the Machine Calculation of Complex Fourier Series,” Mathematics of Computation, Vol.19, No.90, pp.297-301, 1965.
[10] Cochran, William T., et al., “What is the Fast Fourier Transform?,” Proceedings of the IEEE, Vol. 55, No. 10, pp.1664-1674, 1967.
[11] M.C. Pan, Y.F. Lin, “Further Exploration of Vold-Kalman-Filtering Order Tracking with Shaft-Speed Information─I: Theoretical Part, Numerical Implementation and Parameter Investigations,” Mechanical Systems and Signal Processing, Vol. 20, pp. 1134-1154, 2006.
[12] M.C. Pan, Y.F. Lin, “Further Exploration of Vold-Kalman-Filtering Order Tracking with Shaft-Speed Information─II: Engineering Applications,” Mechanical Systems and Signal Processing, Vol. 20, pp. 1410-1428, 2006.
[13] P.C. Tsai, C.C. Cheng, Y.C. Hwang, “Ball Screw Preload Loss Detection Using Ball Pass Frequency,” Mechanical Systems and Signal Processing, Vol. 48, pp. 77-91, 2014.
[14] D. Antory, “Application of a Data-driven Monitoring Technique to Diagnose Air Leaks in an Automotive Diesel Engine: A case Study,” Mechanical Systems and Signal Processing, Vol. 21, pp. 795-808, 2007.
[15] 朱效賢，包絡線分析於軸承故障診斷之探討暨工程應用，國立中央大學機械工程研究所碩士論文，2005。
[16] 曹文昌，適當本質模態函數篩選應用於滾珠軸承故障診斷，國立中央大學機械工程所博士論文，2013。
[17] Y. H. Kim, A. C. Tan, J. Mathew and B. S. Yang, “Condition Monitoring of Low Speed Bearings: a Comparative Study of the Ultrasound Technique Versus Vibration Measurements,” Engineering asset management, pp. 182-191, Springer London, 2006.
[18] B. Li, M. Y. Chow, Y. Tipsuwan and J. C. Hung, “Neural-Network-Based Motor Rolling Bearing Fault Diagnosis ,” IEEE Transactions on Industrial Electronics, Vol. 47, No. 5, pp. 1060-1069, 2000.
[19] T. Kohonen, “The Self-Organizing Map ,” Proceedings of the IEEE, Vol. 78,No. 9, pp. 1464-1480, 1990.
[20] 張斐章，張麗秋，類神經網路導論:原理與應用，滄海出版社，2010
[21] J. Tian, M. H. Azarian and M. Pecht, “Anomaly Detection Using Self-Organizing Maps-Based K-Nearest Neighbor Algorithm,” Proceedings of the European Conference of the Prognostics and Health Management Society, 2014.
[22] S. Subbiah, S. Rosbach, H. Von-Hoersten and S. Turrin, “An Intuitive Diagnostic Model for Gas Analyzers Based on Self-Organizing Maps,” IFAC-PapersOnLine, Vol. 48, pp. 814-819, 2015.
[23] 東培工業，軸承額定負荷與壽命，2013。
[24] 上銀科技，滾珠螺桿技術手冊，2012。
[25] K. Pearson, “LIII. On Lines and Planes of Closest Fit to Systems of Points in Space,” The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 2, No.11, pp.559-572, 1901.
[26] L. Cohen, Time-frequency Analysis, Prentice Hall, New Jersey, 1995.
[27] V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing, Prentice Hall, New Jersey, 1989.
[28] 何正嘉，袁靜，訾豔陽，機械故障診斷的內積變換原理與應用，科學出版社，2012。
[29] S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University press, 2004.
[30] R. A. Fisher, “The Use of Multiple Measurements in Taxonomic Problems,” Annals of eugenics, vol.7, Part II, pp.179-188, 1936.
[31] R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, John Wiley & Sons, 2012.