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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
Fax:
86-571-87239571
Add:
No.9 Gaoguannong,Daxue Road,Hangzhou,China
P.C:
310009
E-mail:
meem_contribute@163.com
Abstract: The mechanical system error of precision machine tools is affected by various factors such as transmission system design, debugging, environmental changes, etc., and belongs to the lack of information system with unknown distribution. Aiming at the evaluation problems of the mechanical system error of precision machine which belonged to poor information of unknown distribution, the parameter and non-parameter fusion method was proposed to assess the performance variation of mechanical system on precision machine. The first of all, in the service time, assessment objectives were constituted by taking at least two order data of products size on precision machine at the different time phase. Then, robust treatment for the assessment objective was conducted by adopting the fusion method of the median and Huber M estimate, order statistics and size characteristics interval were obtained and significance level was determined. Calculated grouping number and cumulative frequency, similarity characteristics of the difference time phases data were evaluated by taking Smirnoff hypothesis test method conducted comparison with the standard statistics. So whether performance variation or not on the precision machine tool were judged. Finally, effectiveness of the methods were tested by precision data of the using two groups data of the special outer rings measuring devices on the bearings at the different time phase. Results show that precision distributions of the 2-time phases are the skew distribution of the 95% significance level, both distribution characteristics is not similarity, so the mechanical system on precision machine have been changed. Unknown distribution and confidence level characteristics of test data can be conquered by systematic using the fusion method of the median and Huber M estimate, Smirnoff hypothesis test, error of mechanical system can be effective analyzed on the above methods. A reliable basis for the performance assessment and maintenance of the precision machine tool complex system is provided.
Key words: precision machine tool; mechanical system error adjustment; transmission system; information-poor system with unknown distribution; median estimation; confidence level; Smirnoff hypothesis
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