本文關(guān)鍵詞： 可靠性 磨削過程 泊松過程 乏信息融合 灰自助 最大熵 模糊集合 非排序灰關(guān)系　出處：《河南科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著機(jī)械制造技術(shù)的發(fā)展,為了使軸承零件達(dá)到更高的技術(shù)要求,滾動(dòng)軸承磨削過程越來越復(fù)雜也越來越難控制,經(jīng)常遇到概率分布未知和小樣本的可靠性分析難題,如果仍采用傳統(tǒng)的統(tǒng)計(jì)學(xué)方法分析滾動(dòng)軸承磨削過程的可靠性,則結(jié)果是不理想的。因此,針對(duì)滾動(dòng)軸承磨削過程的可靠性問題,本課題基于乏信息系統(tǒng)理論,運(yùn)用灰自助原理、最大熵方法、模糊集合理論、泊松過程和非排序灰關(guān)系,對(duì)滾動(dòng)軸承某質(zhì)量參數(shù)進(jìn)行分析,以完成滾動(dòng)軸承磨削過程可靠性評(píng)估。主要分為4個(gè)部分:1融合隸屬函數(shù)法、最大隸屬度法、滾動(dòng)均值法、算術(shù)平均值法和自助法,提出一種乏信息融合技術(shù),以調(diào)整機(jī)床的加工誤差。運(yùn)用該融合技術(shù)融合機(jī)床試加工時(shí)輸出的小樣本數(shù)據(jù),獲取工件的估計(jì)真值,參照估計(jì)真值對(duì)機(jī)床的加工誤差進(jìn)行調(diào)整;運(yùn)用模糊集合理論,在置信水平P=95%的條件下,借助機(jī)床調(diào)整后輸出的小樣本可靠數(shù)據(jù),預(yù)測出工件的估計(jì)區(qū)間,以判斷調(diào)整后機(jī)床的可靠程度。案例研究表明,乏信息融合技術(shù)能夠?qū)崿F(xiàn)機(jī)床加工誤差的調(diào)整,且調(diào)整后的機(jī)床可靠性至少為95%。2針對(duì)滾動(dòng)軸承磨削系統(tǒng)運(yùn)行狀態(tài)的可靠性,推薦一種乏信息評(píng)估方法,以解決小樣本和概率分布未知條件下的可靠性評(píng)估問題�；诠ぜ|(zhì)量檢測的小樣本數(shù)據(jù),用灰自助方法生成大量模擬數(shù)據(jù);用最大熵方法處理大量模擬數(shù)據(jù),構(gòu)建磨削系統(tǒng)運(yùn)行狀態(tài)的概率密度函數(shù);設(shè)定置信水平P,獲取磨削系統(tǒng)運(yùn)行狀態(tài)的置信區(qū)間與擴(kuò)展不確定度;根據(jù)磨削過程中輸出工件的質(zhì)量數(shù)據(jù),通過泊松計(jì)數(shù)過程,計(jì)算磨削系統(tǒng)運(yùn)行狀態(tài)的變異強(qiáng)度;借助泊松過程的無失效概率,得到磨削系統(tǒng)運(yùn)行狀態(tài)的可靠性函數(shù)。案例研究表明,置信水平P為95%是磨削系統(tǒng)實(shí)現(xiàn)良好運(yùn)行狀態(tài)的最佳選擇點(diǎn)。該結(jié)果為合理調(diào)整機(jī)床提供了理論依據(jù)。3基于磨削系統(tǒng)運(yùn)行狀態(tài)可靠性研究,運(yùn)用乏信息評(píng)估方法對(duì)磨削系統(tǒng)運(yùn)行狀態(tài)演變的可靠性進(jìn)行實(shí)時(shí)評(píng)估。獲取多組檢測數(shù)據(jù)序列,在最佳置信水平P=95%下,繪制磨削系統(tǒng)運(yùn)行狀態(tài)演變的可靠性曲線圖,以實(shí)時(shí)預(yù)測磨削系統(tǒng)運(yùn)行狀態(tài)演變的可靠性。案例研究表明,若檢測數(shù)據(jù)的品質(zhì)實(shí)現(xiàn)可靠度r0.65,檢測數(shù)據(jù)與本征數(shù)據(jù)的可靠性概率密度函數(shù)的面積交集A0.3,檢測數(shù)據(jù)的變異概率PB≤0.7,則說明磨削系統(tǒng)運(yùn)行狀態(tài)演變是可靠的,沒有發(fā)生變異;否則,認(rèn)為磨削系統(tǒng)運(yùn)行狀態(tài)演變是不可靠的,其發(fā)生了變異。該結(jié)果為判斷磨削過程是否可靠提供了理論依據(jù)。敏感性分析表明,樣本大小不影響其評(píng)估結(jié)果。4根據(jù)非排序灰關(guān)系和模糊集合理論,對(duì)滾動(dòng)軸承磨削過程的變化程度進(jìn)行評(píng)估。運(yùn)用非排序灰關(guān)系,設(shè)在灰置信水平P=95%下,借助按順序采集的時(shí)間數(shù)據(jù)序列,求解兩個(gè)時(shí)間數(shù)據(jù)序列之間的灰屬性權(quán)重,并構(gòu)建時(shí)間數(shù)據(jù)序列之間的灰屬性權(quán)重相似矩陣;運(yùn)用模糊傳遞閉包法,求解時(shí)間數(shù)據(jù)序列之間的灰屬性權(quán)重等價(jià)矩陣;通過假設(shè)性檢驗(yàn)和分段平均等價(jià)性系數(shù),描述磨床系統(tǒng)誤差的變化過程,以實(shí)現(xiàn)磨削過程變化程度的評(píng)估。案例研究表明,該評(píng)估方法能夠準(zhǔn)確描述磨床系統(tǒng)誤差的變化過程,實(shí)現(xiàn)了磨削過程變化程度的評(píng)估,且評(píng)估結(jié)果與實(shí)際情況相符。
[Abstract]:With the development of manufacturing technology, in order to make the bearing parts meet the requirements of higher technology, rolling bearing grinding process more complex more and more difficult to control, often meet the reliability probability distribution is unknown and small sample problem analysis, if the reliability analysis of rolling bearing grinding process using the traditional statistical methods, the result is not ideal. Therefore, in view of the reliability problem of rolling bearing grinding process, the lack of information system based on the theory, using the principle of Grey Bootstrap, maximum entropy method, fuzzy set theory, Poisson process and non sort grey relation, on some quality parameters of rolling bearings of bearing grinding to complete the process of reliability evaluation is mainly divided into rolling. The 4 part: the 1 fusion method of membership function and the maximum membership degree method, rolling average method, arithmetic mean method and bootstrap method, presents a lack of information fusion technology to adjust Machining error. The use of small sample data output of the fusion fusion machine test processing, the true value of the estimated acquisition work, according to the estimated true value error of machine tool adjustment; using the fuzzy set theory, the confidence level of P=95% under the condition of small sample, reliable data by means of machine tool adjustment output, forecast the interval estimation of the workpiece, to determine the extent of reliable adjusted machine. Case study shows that the lack of information fusion technology can realize the machining error of machine tool adjustment, reliability and adjusted at least 95%.2 reliability for the running state of rolling bearing grinding system, recommended a poor information evaluation method to solve the problem of reliability evaluation of small sample and unknown probability distribution under the condition of small sample data. The quality of workpieces based on detection of a large number of simulation data generated using the method of Grey Bootstrap; using the maximum entropy method. And a lot of simulation data, the probability density function of the construction operation state of grinding system; setting the confidence level P, confidence interval and extended access operation state of grinding system uncertainty; according to the quality of data output workpiece in grinding process, the Poisson process, variation of strength calculation of running state of grinding system; no failure probability with Poisson process the obtained reliability function of running state of grinding system. A case study shows that the confidence level of 95% P is the best choice of point grinding system to achieve good running state. The results for the reasonable adjustment of machine bed provides a theoretical basis for the research of.3 system based on the operation reliability of grinding using the reliability assessment method, lack of information on the evolution of the running state of the grinding system the real time assessment. Access to multiple sets of test data sequences in the optimal confidence level P=95%, drawing the running state of the grinding system modeling The reliability curve of the reliability evolution of the running state of grinding system real-time prediction. A case study shows that if the test data quality achieving reliability r0.65, the testing data and the intrinsic data reliability is the probability density function of the intersection area of A0.3, detection of mutation probability of PB is less than or equal to 0.7 data, the running state of system evolution is grinding reliable, no change; otherwise, that the running state of the grinding system evolution is not reliable, the mutation. The results for the judgment of the grinding process is reliable and provides a theoretical basis. The sensitivity analysis showed that the sample size does not affect the evaluation result of.4 according to the sorting grey relation and fuzzy set theory to evaluate the changes the degree of bearing grinding process of rolling. Using non sort grey relation, a grey confidence level under P=95%, using the time series data according to the order of acquisition, for two hours Grey attribute weights between the data sequence, and construct the grey attribute weights between the time series data of the similar matrix; fuzzy transitive closure method, grey attribute weight equivalent matrix between solution time series data; through hypothesis testing and piecewise average equivalence coefficient, describe the change process of grinder system error, in order to achieve the evaluation of degree of change the grinding process. The case study shows that the change process of the evaluation method can accurately describe the grinder system error, realizes the evaluation of degree of change of the grinding process, and the evaluation results and the actual situation match.

【學(xué)位授予單位】：河南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TH133.33;TG580.6

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 夏新濤;朱文換;陳士忠;;基于乏信息融合技術(shù)的機(jī)床加工誤差的調(diào)整方法[J];中國機(jī)械工程;2016年13期

2 李宏坤;張志新;李秀剛;任遠(yuǎn)杰;;Reliability Prediction Method Based on State Space Model for Rolling Element Bearing[J];Journal of Shanghai Jiaotong University(Science);2015年03期

3 Yi-Kuei Lin;Ping-Chen Chang;;PREDECESSOR-SET TECHNIQUE FOR RELIABILITY EVALUATION OF A STOCHASTIC MANUFACTURING SYSTEM[J];Journal of Systems Science and Systems Engineering;2015年02期

4 夏新濤;孟艷艷;邱明;;用灰自助泊松方法預(yù)測滾動(dòng)軸承振動(dòng)性能可靠性的變異過程[J];機(jī)械工程學(xué)報(bào);2015年09期

5 夏新濤;秦園園;邱明;;基于灰關(guān)系的制造過程穩(wěn)定性評(píng)估[J];航空動(dòng)力學(xué)報(bào);2015年03期

6 夏新濤;秦園園;邱明;;基于灰自助最大熵法的機(jī)床加工誤差的調(diào)整[J];中國機(jī)械工程;2014年17期

7 何益海;沈珍;尹超;;基于過程質(zhì)量數(shù)據(jù)的制造系統(tǒng)可靠性建模分析[J];北京航空航天大學(xué)學(xué)報(bào);2014年08期

8 謝里陽;劉建中;吳寧祥;錢文學(xué);;風(fēng)電裝備傳動(dòng)系統(tǒng)及零部件疲勞可靠性評(píng)估方法[J];機(jī)械工程學(xué)報(bào);2014年11期

9 夏新濤;尚艷濤;金銀平;祝世超;邱明;;基于多權(quán)重法的機(jī)械產(chǎn)品品質(zhì)實(shí)現(xiàn)可靠性分析[J];中國機(jī)械工程;2013年22期

10 傅蔡安;張明;;軸承鋼球微觀磨粒磨削過程的數(shù)值模擬[J];軸承;2010年11期

相關(guān)博士學(xué)位論文 前2條

1 柳劍;制造系統(tǒng)運(yùn)行可靠性分析與維修保障策略研究[D];重慶大學(xué);2014年

2 夏新濤;滾動(dòng)軸承乏信息試驗(yàn)評(píng)估方法及其應(yīng)用技術(shù)研究[D];上海大學(xué);2008年

相關(guān)碩士學(xué)位論文 前2條

1 秦園園;滾動(dòng)軸承制造過程中的乏信息工藝驗(yàn)證[D];河南科技大學(xué);2015年

2 張恒;基于元?jiǎng)幼鞯臄?shù)控機(jī)床可靠性分析與控制技術(shù)研究[D];重慶大學(xué);2012年

，

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