重型數(shù)控銑鏜床鏜軸進(jìn)給機(jī)構(gòu)的可靠性研究
發(fā)布時(shí)間：2018-07-17 08:49
【摘要】：重型數(shù)控機(jī)床是大型基礎(chǔ)零部件的關(guān)鍵加工設(shè)備,其核心傳動(dòng)系統(tǒng)從根本上制約著機(jī)床的功能輸出和加工質(zhì)量,其核心傳動(dòng)系統(tǒng)的可靠性問(wèn)題直接影響著整機(jī)技術(shù)性能的體現(xiàn),并已成為其進(jìn)入世界領(lǐng)先水平的難題之一。重型數(shù)控銑鏜床作為重型數(shù)控機(jī)床的主要成員之一,其核心傳動(dòng)子系統(tǒng)鏜軸進(jìn)給機(jī)構(gòu)的可靠性分析實(shí)際工程意義顯著。重型數(shù)控機(jī)床在現(xiàn)場(chǎng)服役期間,機(jī)械零部件的性能往往會(huì)逐漸降低直至失效,進(jìn)而影響整機(jī)的性能,于是零部件與系統(tǒng)均會(huì)呈現(xiàn)出多態(tài)性。而傳統(tǒng)的故障樹(shù)分析是建立在二態(tài)假設(shè)的基礎(chǔ)上的,無(wú)法對(duì)重型數(shù)控機(jī)床整機(jī)及零部件的多態(tài)性進(jìn)行有效地描述和分析。因此,本文運(yùn)用多狀態(tài)故障樹(shù)理論技術(shù),從以下幾個(gè)方面對(duì)鏜軸進(jìn)給機(jī)構(gòu)的可靠性分析技術(shù)展開(kāi)研究。首先,對(duì)鏜軸進(jìn)給機(jī)構(gòu)的基本功能、結(jié)構(gòu)組成以及工作環(huán)境的特殊性進(jìn)行深入分析。在此基礎(chǔ)上,對(duì)系統(tǒng)及其零部件進(jìn)行狀態(tài)定義。為突破傳統(tǒng)分析中將系統(tǒng)分解成若干個(gè)二態(tài)子系統(tǒng)或部件來(lái)進(jìn)行分析的假設(shè)缺陷,本文運(yùn)用由多狀態(tài)可靠性框圖生成多狀態(tài)故障樹(shù)的建模方法,采用由各子系統(tǒng)到系統(tǒng)整機(jī)逐層向上的方式,建立鏜軸進(jìn)給機(jī)構(gòu)的多狀態(tài)可靠性框圖及其多狀態(tài)故障樹(shù)。然后,對(duì)鏜軸進(jìn)給機(jī)構(gòu)的多狀態(tài)故障樹(shù)進(jìn)行定量分析。本文分別運(yùn)用多值決策圖與貝葉斯網(wǎng)絡(luò)方法,采用逐層向上的分析求解方法,依次求得各子系統(tǒng)頂事件各狀態(tài)的發(fā)生概率,直至鏜軸進(jìn)給機(jī)構(gòu)各狀態(tài)的發(fā)生概率;在此基礎(chǔ)上,對(duì)多值決策圖與貝葉斯網(wǎng)絡(luò)分析方法的優(yōu)劣進(jìn)行比較分析。進(jìn)一步地,本文提出基于貝葉斯網(wǎng)絡(luò)的重要度分析方法,來(lái)對(duì)鏜軸進(jìn)給機(jī)構(gòu)及其各子系統(tǒng)多狀態(tài)故障樹(shù)底事件的概率重要度以及關(guān)鍵重要度進(jìn)行計(jì)算;并通過(guò)對(duì)重要度計(jì)算結(jié)果進(jìn)行分析,尋找系統(tǒng)的薄弱環(huán)節(jié),為系統(tǒng)的改進(jìn)提供依據(jù)。最后,考慮到多狀態(tài)系統(tǒng)中共因失效的影響以及可靠性信息的不確定性,本文將模糊概率與共因失效引入貝葉斯網(wǎng)絡(luò)來(lái)開(kāi)展多狀態(tài)故障樹(shù)分析方法的研究。采用基于貝葉斯網(wǎng)絡(luò)的共因失效建模方法,建立鏜軸進(jìn)給機(jī)構(gòu)的共因失效-貝葉斯網(wǎng)絡(luò)模型。為了突破該模型的求解,首先通過(guò)引入模糊集理論,運(yùn)用三角模糊數(shù)來(lái)描述根節(jié)點(diǎn)各狀態(tài)的發(fā)生概率,并提出運(yùn)用解模糊與歸一化方法,以此來(lái)求解擁有重復(fù)事件的故障樹(shù)頂事件各狀態(tài)的發(fā)生概率。并在此基礎(chǔ)上,對(duì)鏜軸進(jìn)給機(jī)構(gòu)的共因失效-貝葉斯網(wǎng)絡(luò)模型進(jìn)行雙向推理,識(shí)別并確認(rèn)共因失效對(duì)系統(tǒng)可靠性的影響,為系統(tǒng)改進(jìn)提供實(shí)用信息支撐。
[Abstract]:Heavy CNC machine tool is the key processing equipment of large basic parts. Its core transmission system fundamentally restricts the function output and machining quality of machine tool. The reliability of its core transmission system directly affects the embodiment of the technical performance of the whole machine. And it has become one of the difficulties in entering the world's leading level. As one of the main members of heavy-duty NC machine tool, the reliability analysis of the boring shaft feed mechanism of the core transmission subsystem of heavy NC milling and boring machine is of great significance in practical engineering. During the field service of heavy duty CNC machine tools, the performance of mechanical parts will decrease gradually until failure, and then affect the performance of the whole machine, so parts and systems will show polymorphism. However, the traditional fault tree analysis is based on the two-state hypothesis, which can not effectively describe and analyze the polymorphism of the whole machine parts and components of heavy NC machine tools. Therefore, in this paper, the reliability analysis technology of boring shaft feeding mechanism is studied from the following aspects by using multi-state fault tree theory. Firstly, the basic function, structure composition and working environment particularity of the boring shaft feed mechanism are analyzed. On this basis, the state of the system and its components are defined. In order to break through the hypothetical defect of decomposing the system into several two-state subsystems or components in traditional analysis, this paper uses the modeling method of generating multi-state fault tree from multi-state reliability block diagram. The multi-state reliability block diagram of boring shaft feeding mechanism and its multi-state fault tree are established by adopting the way from each subsystem to the whole system. Then, the multi-state fault tree of boring shaft feed mechanism is quantitatively analyzed. In this paper, by using multi-valued decision diagram and Bayesian network method, the probability of occurrence of each state of the top event of each subsystem is obtained in turn, and the probability of occurrence of each state of the boring axis feeding mechanism is obtained in turn by using the method of analysis and solution up to the level, and based on this, the probability of occurrence of each state of the boring axis feeding mechanism is obtained. The advantages and disadvantages of multi-valued decision graph and Bayesian network analysis method are compared and analyzed. Furthermore, the importance analysis method based on Bayesian network is proposed to calculate the probability importance and critical importance of the multi-state fault tree bottom event of the boring shaft feeding mechanism and its subsystems. By analyzing the results of importance calculation, the weak links of the system are found and the basis for the improvement of the system is provided. Finally, considering the influence of co-failure and uncertainty of reliability information, fuzzy probability and common cause failure are introduced into Bayesian network to study the method of multi-state fault tree analysis. A common-factor failure modeling method based on Bayesian network is used to establish a common-factor failure-Bayesian network model of boring shaft feeding mechanism. In order to break through the solution of the model, firstly, by introducing fuzzy set theory, using triangular fuzzy number to describe the occurrence probability of each state of root node, and putting forward the method of solving fuzzy and normalizing. In this way, the probability of occurrence of each state of the fault tree top event with repeated events is solved. On this basis, the common-factor invalidation-Bayesian network model of the boring shaft feeding mechanism is inferred, and the effect of common cause failure on the reliability of the system is recognized and confirmed, which provides practical information support for the improvement of the system.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TG659
本文編號(hào)：2129876
[Abstract]:Heavy CNC machine tool is the key processing equipment of large basic parts. Its core transmission system fundamentally restricts the function output and machining quality of machine tool. The reliability of its core transmission system directly affects the embodiment of the technical performance of the whole machine. And it has become one of the difficulties in entering the world's leading level. As one of the main members of heavy-duty NC machine tool, the reliability analysis of the boring shaft feed mechanism of the core transmission subsystem of heavy NC milling and boring machine is of great significance in practical engineering. During the field service of heavy duty CNC machine tools, the performance of mechanical parts will decrease gradually until failure, and then affect the performance of the whole machine, so parts and systems will show polymorphism. However, the traditional fault tree analysis is based on the two-state hypothesis, which can not effectively describe and analyze the polymorphism of the whole machine parts and components of heavy NC machine tools. Therefore, in this paper, the reliability analysis technology of boring shaft feeding mechanism is studied from the following aspects by using multi-state fault tree theory. Firstly, the basic function, structure composition and working environment particularity of the boring shaft feed mechanism are analyzed. On this basis, the state of the system and its components are defined. In order to break through the hypothetical defect of decomposing the system into several two-state subsystems or components in traditional analysis, this paper uses the modeling method of generating multi-state fault tree from multi-state reliability block diagram. The multi-state reliability block diagram of boring shaft feeding mechanism and its multi-state fault tree are established by adopting the way from each subsystem to the whole system. Then, the multi-state fault tree of boring shaft feed mechanism is quantitatively analyzed. In this paper, by using multi-valued decision diagram and Bayesian network method, the probability of occurrence of each state of the top event of each subsystem is obtained in turn, and the probability of occurrence of each state of the boring axis feeding mechanism is obtained in turn by using the method of analysis and solution up to the level, and based on this, the probability of occurrence of each state of the boring axis feeding mechanism is obtained. The advantages and disadvantages of multi-valued decision graph and Bayesian network analysis method are compared and analyzed. Furthermore, the importance analysis method based on Bayesian network is proposed to calculate the probability importance and critical importance of the multi-state fault tree bottom event of the boring shaft feeding mechanism and its subsystems. By analyzing the results of importance calculation, the weak links of the system are found and the basis for the improvement of the system is provided. Finally, considering the influence of co-failure and uncertainty of reliability information, fuzzy probability and common cause failure are introduced into Bayesian network to study the method of multi-state fault tree analysis. A common-factor failure modeling method based on Bayesian network is used to establish a common-factor failure-Bayesian network model of boring shaft feeding mechanism. In order to break through the solution of the model, firstly, by introducing fuzzy set theory, using triangular fuzzy number to describe the occurrence probability of each state of root node, and putting forward the method of solving fuzzy and normalizing. In this way, the probability of occurrence of each state of the fault tree top event with repeated events is solved. On this basis, the common-factor invalidation-Bayesian network model of the boring shaft feeding mechanism is inferred, and the effect of common cause failure on the reliability of the system is recognized and confirmed, which provides practical information support for the improvement of the system.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TG659
【參考文獻(xiàn)】
相關(guān)期刊論文 前3條
1 陸瑩;李啟明;周志鵬;;基于模糊貝葉斯網(wǎng)絡(luò)的地鐵運(yùn)營(yíng)安全風(fēng)險(xiǎn)預(yù)測(cè)[J];東南大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年05期
2 周忠寶;馬超群;周經(jīng)倫;董豆豆;;基于貝葉斯網(wǎng)絡(luò)的多態(tài)故障樹(shù)分析方法[J];數(shù)學(xué)的實(shí)踐與認(rèn)識(shí);2008年19期
3 曾亮,郭欣;多狀態(tài)系統(tǒng)元件重要度定義及其計(jì)算[J];系統(tǒng)工程與電子技術(shù);1999年05期
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