Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method
المؤلفون المشاركون
Huang, Zhonghua
Liu, Guiping
Li, Jianhua
Mao, Wengui
Hu, Chaoliang
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-07-29
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
As a kind of rotor system, the electric spindle system is the core component of the precision grinding machine.
The vibration caused by the mass imbalance is the main factor that causes the vibration of the grinding machine.
Identifying the eccentricity parameters in an electric spindle system is a key issue in eliminating mass imbalances.
It is difficult for engineers to understand the approximate range of eccentricity by experience; that is, it is difficult to obtain a priori information about eccentricity.
At the same time, due to the geometric characteristics of the electrospindle system, the material factors and the randomness of the measurement response, these uncertain factors, even in a small case, are likely to cause large deviations in the eccentricity recognition results.
The search algorithm used in the maximum likelihood method to identify the eccentricity parameters of the electrospindle system is computationally intensive, and the sensitivity in the iterative process brings some numerical problems.
This paper introduces an Advance-Retreat Method (ARM) of the search interval to the maximum likelihood method, the unknown parameter increment obtained by the maximum likelihood method is used as the step size in the iteration, and the Advance-Retreat Method of the search interval is used to adjust the next design point so that the objective function value is gradually decreasing.
The recognition results under the three kinds of measurement errors show that the improved maximum likelihood method improves the recognition effect of the maximum likelihood method and can reduce the influence of uncertainty factors on the recognition results, and the robustness is satisfactory.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Mao, Wengui& Hu, Chaoliang& Li, Jianhua& Huang, Zhonghua& Liu, Guiping. 2020. Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method. Shock and Vibration،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1210022
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Mao, Wengui…[et al.]. Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method. Shock and Vibration No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1210022
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Mao, Wengui& Hu, Chaoliang& Li, Jianhua& Huang, Zhonghua& Liu, Guiping. Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1210022
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1210022
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر