基于FTF方法的无人机液压与冷气系统可靠性分析
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摘要
近百年来,无人机的发展经历了最初问世到广泛应用的过程,由于其自身特点和优越性能,它在各国航空领域的地位愈显重要,随着无人机技术高端化和先进化,其组成和系统越来越复杂,而由于受操作技术的熟练性和远程遥控的超长性影响,无人机重大事故经常发生,为了避免事故发生,可靠性工作尤显重要,我们在早期就应该做好其可靠性工作,做到防患于未然。
飞机液压与冷气系统故障是各种飞机常见的多发性故障,对整机危害严重。液压与冷气系统也是无人机重要组成部分,对其故障模式进行系统分析以提高可靠性从而降低无人机飞行风险是本论文的主要研究内容,FMECA和FTA是分析产品故障因果关系的常用技术,FMECA是一种上行的追踪,而FTA是下行的分解,这两种分析方法各有优缺点,将两种分析方法结合起来使用的FTF方法是根据被分析对象的复杂程度和约定层次要求,以及时间和费用限制等条件,综合FMECA和FTA对其故障模式进行分析,找出薄弱环节,改进产品设计的一种有效方法。本论文采取FTF方法对无人机液压与冷气系统进行故障分析,找出故障原因,并提出预防措施。
在FMECA分析中,论文介绍了FMECA分析的原理步骤及注意事项,在FTA分析中,本论文介绍了传统FTA分析方法和模糊FTA分析方法的相关内容,并在主液压与冷气系统的FTA分析中提出了T-S模糊门的建树方法以计算不同故障程度发生的模糊可能性。
最后本论文简单介绍了结合FMECA、FTA和FRACAS方法的3F可靠性分析系统以及报警模块的构成和应用。
Recent hundreds of years, the development of Unmanned Aerial Vehicle (UAV) experienced a process which is from first appeared to extensive application. Because of own characteristics and superior performance, its status of all countries in the aerospace sector become more and more important. With UAV technology high-end and advanced, its composition and system become more and more complex, and it will be easily affected by some factors such as longdistance of remote control and operating skills, so UAV’s accidents occurs frequently, in order to avoid the accidents, the reliability work on UAV is particularly important, we should do this early, to fix it before it breaks.
The fault of hydraulic and air conditioning system of aircraft is all sorts of aircraft common fault, if happens, it will be dangerous for the aircraft. Hydraulic and air conditioning system is an important part of UAV, the main research of this paper is to analyse the failure mode of the system and improve the reliability of the system so as to reduce the flight risk of the UAV. FMECA and FTA are two commonly used technology to analyse relationship of product and its fault, FMECA is a tracing way from below, and the FTA is a decomposition method from top down, two analysis methods have their advantages and disadvantages, FTF method which combines two kinds of analysis method is based on the complexity of the analysis object, agreed time and cost requirements, then comprehensive FMECA and FTA to analyse, its aim is to find out the weak link, improve product designing, it’s an effective method to improve the reliability of the product.Using FTF method we analyse failure mode of hydraulic and air conditioning system of UAV to find fault reasons then put forward the preventive measures.
In FMECA analysis, this paper introduces the principle of FMECA analysis steps , matters and needing attention. In the FTA analysis, the paper introduces the conventional fault tree analysis method and the fuzzy fault tree analysis. In the main hydraulic and air conditioning system FTA analysis, T-S fuzzy door tree-building method is introduced to calculate the fuzzy fault degree happen different possibilities.
Finally 3F reliability analysis system which is based on FMECA, FTA and FRACAS is simply described in this paper, besides the structure and application of alarm module is introduced.
飞机液压与冷气系统故障是各种飞机常见的多发性故障,对整机危害严重。液压与冷气系统也是无人机重要组成部分,对其故障模式进行系统分析以提高可靠性从而降低无人机飞行风险是本论文的主要研究内容,FMECA和FTA是分析产品故障因果关系的常用技术,FMECA是一种上行的追踪,而FTA是下行的分解,这两种分析方法各有优缺点,将两种分析方法结合起来使用的FTF方法是根据被分析对象的复杂程度和约定层次要求,以及时间和费用限制等条件,综合FMECA和FTA对其故障模式进行分析,找出薄弱环节,改进产品设计的一种有效方法。本论文采取FTF方法对无人机液压与冷气系统进行故障分析,找出故障原因,并提出预防措施。
在FMECA分析中,论文介绍了FMECA分析的原理步骤及注意事项,在FTA分析中,本论文介绍了传统FTA分析方法和模糊FTA分析方法的相关内容,并在主液压与冷气系统的FTA分析中提出了T-S模糊门的建树方法以计算不同故障程度发生的模糊可能性。
最后本论文简单介绍了结合FMECA、FTA和FRACAS方法的3F可靠性分析系统以及报警模块的构成和应用。
Recent hundreds of years, the development of Unmanned Aerial Vehicle (UAV) experienced a process which is from first appeared to extensive application. Because of own characteristics and superior performance, its status of all countries in the aerospace sector become more and more important. With UAV technology high-end and advanced, its composition and system become more and more complex, and it will be easily affected by some factors such as longdistance of remote control and operating skills, so UAV’s accidents occurs frequently, in order to avoid the accidents, the reliability work on UAV is particularly important, we should do this early, to fix it before it breaks.
The fault of hydraulic and air conditioning system of aircraft is all sorts of aircraft common fault, if happens, it will be dangerous for the aircraft. Hydraulic and air conditioning system is an important part of UAV, the main research of this paper is to analyse the failure mode of the system and improve the reliability of the system so as to reduce the flight risk of the UAV. FMECA and FTA are two commonly used technology to analyse relationship of product and its fault, FMECA is a tracing way from below, and the FTA is a decomposition method from top down, two analysis methods have their advantages and disadvantages, FTF method which combines two kinds of analysis method is based on the complexity of the analysis object, agreed time and cost requirements, then comprehensive FMECA and FTA to analyse, its aim is to find out the weak link, improve product designing, it’s an effective method to improve the reliability of the product.Using FTF method we analyse failure mode of hydraulic and air conditioning system of UAV to find fault reasons then put forward the preventive measures.
In FMECA analysis, this paper introduces the principle of FMECA analysis steps , matters and needing attention. In the FTA analysis, the paper introduces the conventional fault tree analysis method and the fuzzy fault tree analysis. In the main hydraulic and air conditioning system FTA analysis, T-S fuzzy door tree-building method is introduced to calculate the fuzzy fault degree happen different possibilities.
Finally 3F reliability analysis system which is based on FMECA, FTA and FRACAS is simply described in this paper, besides the structure and application of alarm module is introduced.
引文
[1]中国人民解放军总装备部.GJB451A-2005 .可靠性维修性保障性术语. 2005.
[2] Kara-Zaitri C, Keller A Z, Barody I. An improved FMEA methodology. Proceeding Annual Reliability and Maintenance Symposium. Orlando: IEEE 1991, 248-252.
[3] Price C J, Taylor N S. FMEA for multiple failures. Proceedings Annual Reliability and Maintainability Symposium. Anaheim: IEEE, 1998, 43-47.
[4] Seung J Rhee, Kosuke Ishii. Using cost based FMEA to enhance reliability and serviceability. Advanced Engineering Informatics 2003(17):179-188.
[5] W M Goble, A C Brombacher. Using a failure modes, effects and diagnostic Analysis(FMEDA) to measure diagnostic coverage in programmable electronic systems. Reliability Engineering and System Safety, 1999(66):145-148.
[6]胡玺良,张代胜,刘焕广.探析基于寿命成本的FMEA.现代机械, 2007, (1): 4-7.
[7] Chiou C C, Tsai J, Fang Y S. A modified FTA-FMECA methodology: an application for CNT-BL U of TFT-LCD. Proceedings International Conference on New Trends in Informat- ion and Service Science. Beijing: IEEE, 2009, 250-255.
[8] P A A Garcia, R Schirru&P F, Futuoso E melo. A fuzzy data envelopment analysis approach for FMECA. Progress in Nuclear Energy, 2005, 46(3-4):359-373.
[9] Blivband Z, Grabov P Nakar O. Expanded FMEA (EFMEA). Proceedings AnnualReliability and Maintenance Symposium. IEEE, 2004, 31-36.
[10] Shahin A. Integration of FMEA and the Kano model-An exploratory examination. International Journal of Quality & Reliability Management, 2004, 21(7): 731-746.
[11] Pelaez C E, Bowles J B. Using fuzzy logic for system criticality analysis. Proceedings Annual Reliability and Maintainability Symposium. Anaheim: IEEE, 1994, 449-455.
[12]崔文彬,吴桂涛,孙培廷.基于FMEA和模糊综合判断的船舶安全评估.哈尔滨工程大学学报, 2007, 25(3):263-267.
[13]任荣权,于博生,赵众等.失效严重度模糊综合评判.石油学报, 1997, l8(2):138-142.
[14] Russomanno D J, Bonnell R D, Bowles J B. A blackboard model of an effects analysis. IEEE Proeeeding Annual Reliability and Maintenanee 1992, 483-490.
[15] Bell D, Cox L, Jackson S, Schaefer P. Using causal reasoning for automated failure and effectsanalysis (FMEA). Proceedings of Annual Reliability and Maintainability Symposium. Las Vegas:IEEE, 1992, 343-353.
[16] G ABDUL-NOUR, H BEAUDOIN, etc. Reliability based maintenance Policy: A Case Study. The 22nd 1CC&IE Conference. 1998, 35:591-594.
[17] Joseph Barkai. Automatic generation of a diagnostic expert system from failure mode and effects analysis FMEA information, International Congress and Exposition Detroit, Michigan, 1999, 1-7.
[18] Xu K, Tang L C, Xie M, et al. Fuzzy assessment of FMEA for engine systems. Reliability Engineering and System Safety, 2002, 75(1): 17-29.
[19]史宪铭,王华伟.基于贝叶斯网络的复杂系统FMEA模型.网络信息技术, 2004, 23(2): 27-29.
[20]张振夯,基于网络的故障模式影响及致命度分析研究:[硕士学位论文].大连:大连理工大学, 2003.
[21]张海,钱彦岭,邱静.基于功能角色模型的反馈系统故障模式影响分析.国防科技大学学报, 2004, 26(l):99-102.
[22] Gmytrasiewicz. P, Hassberger J A, J C Lee. Fault tree based diagnostics using fuzzy logic. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 1990, 1-2.
[23] Singer D. A fuzzy set approach to fault trees and reliability analysis. Fuzzy Sets and Systems, 1990(34):145-155.
[24] Krishna B Misra, Gunter G Weber, A new method for fuzzy fault tree analysis. Microelectron and Reliability, 1989, 29(2):195-216.
[25]李延杰.故障树分析中的模糊概率重要度.系统工程理论与实践, 1990, 1: 9-12.
[26] Joanne Bechta Dugan, Salvatore Bavuso and Mark Boud. Dynamie fault tree models for fault tolerant computer systems, IEEE Transactions on Reliability, 1992,41(3):363-377.
[27] F A Patterson-Hine, Joanne Bechta Dugan. Modular techinques for dynamic fault-tree analysis, Proceedings Annual Reliability and Maintainability Symposium, 1992, 363-369.
[28] Suprasad Amari, A new approach to solve dynamic fault trees, Reiliability and Maintainability Symposium, 2003,2(28):374-379.
[29] Boudali H, Dugan J B. A discrete time bayesian network reliability modeling and analysis framework. Reliability Engineering and System Safety, 2005, 87:337-349.
[30] Montani S, Portinale L, Bobbio A. Dynamic bayesian networks for modeling advanced fault tree features in dependability analysis. European Safety and Reliability Conferrence, Tri City,Poland:2005.
[31]刘永葆. FTF方法在舰用燃气轮机失效分析中的应用研究.武汉:海军工程大学学报, 1996,1(2):23-26.
[32]杨田,周密,谢俊.正向FTF方法在核级先导式安全阀故障分析中的应用.核动力工程, 2010, 31(1): 65-69.
[33]康锐. FMECA技术及其应用.北京:国防工业出版社. 2006.
[34] GJB450A-2004.装备可靠性工作要求. 2004.
[35]王青. FMEA在航空供应链中的应用探索.航空制造技术. 2008(5):58-61.
[36]陈娟,邓东晓. FMEA质量理念及应用研究.质量技术. 2004(9):20-22.
[37]朱向明,周凤岐,陈俊吉.防空空导弹飞行试验控制系统故障模式研究.弹箭与制导学报. 2009, 29(4):273-276.
[38]赵俊豪.基于模糊FMEA的实习船主机燃油系统安全评估:[硕士学位论文].大连:大连海事大,2007.
[39] H Tanaka, L T Fan, F S Lai, K Touguchi. Fault-tree analysis by fuzzy probability.IEEE Transctions on Reliability. 1983,5(1):18-32.
[40]樊馨月,王杰.电力电子系统故障诊断技术浅谈.电气自动化. 2006,28(5):6-11.
[41]陈海光,程显毅.随机模糊故障树分析方法及应用.计算机工程与应用. 2008, 44(27):229-230.
[42]周瑞平.故障树分析法(FTA)在港口机械维修中的应用.港口装卸. 1999(1).
[43]魏选平,卞树檀.故障树分析法及其应用.计算机科学与技术. 2004,1(3):43-45.
[44]宋保维.系统可靠性设计与分析.西安:西北工业大学出版社. 2008,117-136.
[45]黄洪钟.机械设计模糊优化原理及应用.北京:科学出版社. 1997,32-33.
[46] GJB 1391-92,故障模式、影响及危害性分析程序.
[47]朱继洲.故障树原理及应用.西安:西安交通大学出版社, 1989, 25-28.
[48]李雅武,乜庆海,杨沛.液压系统常见的故障诊断及处理.汽轮机技术, 2005, 47(1): 73-75.
[49]陈新响,李文华,李振中,魏德宝,王国有,周学军.液压系统主要故障分析及对策.液压气动与密封, 2007, (2): 6-7.
[50] Takagi, Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Tram.Syst, Man and Cybern, 1985, 15:116-132.
[51]王哲.链条锅炉燃烧模糊预测控制系统[硕士学位论文].北京:北京科技大学, 2009.
[52]宋华,张洪钺,王行仁. T-S模糊故障树分析方法.控制与决策, 2005, 20(8):854-859.
[53]姚成玉,赵静一.基于T-S模型的液压系统故障树分析方法研究.中国机械工程, 2009,20(16):1913-1917.
[54]李淑庆,张根保,任显林,李劼.基于3F技术的产品可靠性工程研究.现代制造工程, 2007(3):5-7.
[2] Kara-Zaitri C, Keller A Z, Barody I. An improved FMEA methodology. Proceeding Annual Reliability and Maintenance Symposium. Orlando: IEEE 1991, 248-252.
[3] Price C J, Taylor N S. FMEA for multiple failures. Proceedings Annual Reliability and Maintainability Symposium. Anaheim: IEEE, 1998, 43-47.
[4] Seung J Rhee, Kosuke Ishii. Using cost based FMEA to enhance reliability and serviceability. Advanced Engineering Informatics 2003(17):179-188.
[5] W M Goble, A C Brombacher. Using a failure modes, effects and diagnostic Analysis(FMEDA) to measure diagnostic coverage in programmable electronic systems. Reliability Engineering and System Safety, 1999(66):145-148.
[6]胡玺良,张代胜,刘焕广.探析基于寿命成本的FMEA.现代机械, 2007, (1): 4-7.
[7] Chiou C C, Tsai J, Fang Y S. A modified FTA-FMECA methodology: an application for CNT-BL U of TFT-LCD. Proceedings International Conference on New Trends in Informat- ion and Service Science. Beijing: IEEE, 2009, 250-255.
[8] P A A Garcia, R Schirru&P F, Futuoso E melo. A fuzzy data envelopment analysis approach for FMECA. Progress in Nuclear Energy, 2005, 46(3-4):359-373.
[9] Blivband Z, Grabov P Nakar O. Expanded FMEA (EFMEA). Proceedings AnnualReliability and Maintenance Symposium. IEEE, 2004, 31-36.
[10] Shahin A. Integration of FMEA and the Kano model-An exploratory examination. International Journal of Quality & Reliability Management, 2004, 21(7): 731-746.
[11] Pelaez C E, Bowles J B. Using fuzzy logic for system criticality analysis. Proceedings Annual Reliability and Maintainability Symposium. Anaheim: IEEE, 1994, 449-455.
[12]崔文彬,吴桂涛,孙培廷.基于FMEA和模糊综合判断的船舶安全评估.哈尔滨工程大学学报, 2007, 25(3):263-267.
[13]任荣权,于博生,赵众等.失效严重度模糊综合评判.石油学报, 1997, l8(2):138-142.
[14] Russomanno D J, Bonnell R D, Bowles J B. A blackboard model of an effects analysis. IEEE Proeeeding Annual Reliability and Maintenanee 1992, 483-490.
[15] Bell D, Cox L, Jackson S, Schaefer P. Using causal reasoning for automated failure and effectsanalysis (FMEA). Proceedings of Annual Reliability and Maintainability Symposium. Las Vegas:IEEE, 1992, 343-353.
[16] G ABDUL-NOUR, H BEAUDOIN, etc. Reliability based maintenance Policy: A Case Study. The 22nd 1CC&IE Conference. 1998, 35:591-594.
[17] Joseph Barkai. Automatic generation of a diagnostic expert system from failure mode and effects analysis FMEA information, International Congress and Exposition Detroit, Michigan, 1999, 1-7.
[18] Xu K, Tang L C, Xie M, et al. Fuzzy assessment of FMEA for engine systems. Reliability Engineering and System Safety, 2002, 75(1): 17-29.
[19]史宪铭,王华伟.基于贝叶斯网络的复杂系统FMEA模型.网络信息技术, 2004, 23(2): 27-29.
[20]张振夯,基于网络的故障模式影响及致命度分析研究:[硕士学位论文].大连:大连理工大学, 2003.
[21]张海,钱彦岭,邱静.基于功能角色模型的反馈系统故障模式影响分析.国防科技大学学报, 2004, 26(l):99-102.
[22] Gmytrasiewicz. P, Hassberger J A, J C Lee. Fault tree based diagnostics using fuzzy logic. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 1990, 1-2.
[23] Singer D. A fuzzy set approach to fault trees and reliability analysis. Fuzzy Sets and Systems, 1990(34):145-155.
[24] Krishna B Misra, Gunter G Weber, A new method for fuzzy fault tree analysis. Microelectron and Reliability, 1989, 29(2):195-216.
[25]李延杰.故障树分析中的模糊概率重要度.系统工程理论与实践, 1990, 1: 9-12.
[26] Joanne Bechta Dugan, Salvatore Bavuso and Mark Boud. Dynamie fault tree models for fault tolerant computer systems, IEEE Transactions on Reliability, 1992,41(3):363-377.
[27] F A Patterson-Hine, Joanne Bechta Dugan. Modular techinques for dynamic fault-tree analysis, Proceedings Annual Reliability and Maintainability Symposium, 1992, 363-369.
[28] Suprasad Amari, A new approach to solve dynamic fault trees, Reiliability and Maintainability Symposium, 2003,2(28):374-379.
[29] Boudali H, Dugan J B. A discrete time bayesian network reliability modeling and analysis framework. Reliability Engineering and System Safety, 2005, 87:337-349.
[30] Montani S, Portinale L, Bobbio A. Dynamic bayesian networks for modeling advanced fault tree features in dependability analysis. European Safety and Reliability Conferrence, Tri City,Poland:2005.
[31]刘永葆. FTF方法在舰用燃气轮机失效分析中的应用研究.武汉:海军工程大学学报, 1996,1(2):23-26.
[32]杨田,周密,谢俊.正向FTF方法在核级先导式安全阀故障分析中的应用.核动力工程, 2010, 31(1): 65-69.
[33]康锐. FMECA技术及其应用.北京:国防工业出版社. 2006.
[34] GJB450A-2004.装备可靠性工作要求. 2004.
[35]王青. FMEA在航空供应链中的应用探索.航空制造技术. 2008(5):58-61.
[36]陈娟,邓东晓. FMEA质量理念及应用研究.质量技术. 2004(9):20-22.
[37]朱向明,周凤岐,陈俊吉.防空空导弹飞行试验控制系统故障模式研究.弹箭与制导学报. 2009, 29(4):273-276.
[38]赵俊豪.基于模糊FMEA的实习船主机燃油系统安全评估:[硕士学位论文].大连:大连海事大,2007.
[39] H Tanaka, L T Fan, F S Lai, K Touguchi. Fault-tree analysis by fuzzy probability.IEEE Transctions on Reliability. 1983,5(1):18-32.
[40]樊馨月,王杰.电力电子系统故障诊断技术浅谈.电气自动化. 2006,28(5):6-11.
[41]陈海光,程显毅.随机模糊故障树分析方法及应用.计算机工程与应用. 2008, 44(27):229-230.
[42]周瑞平.故障树分析法(FTA)在港口机械维修中的应用.港口装卸. 1999(1).
[43]魏选平,卞树檀.故障树分析法及其应用.计算机科学与技术. 2004,1(3):43-45.
[44]宋保维.系统可靠性设计与分析.西安:西北工业大学出版社. 2008,117-136.
[45]黄洪钟.机械设计模糊优化原理及应用.北京:科学出版社. 1997,32-33.
[46] GJB 1391-92,故障模式、影响及危害性分析程序.
[47]朱继洲.故障树原理及应用.西安:西安交通大学出版社, 1989, 25-28.
[48]李雅武,乜庆海,杨沛.液压系统常见的故障诊断及处理.汽轮机技术, 2005, 47(1): 73-75.
[49]陈新响,李文华,李振中,魏德宝,王国有,周学军.液压系统主要故障分析及对策.液压气动与密封, 2007, (2): 6-7.
[50] Takagi, Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Tram.Syst, Man and Cybern, 1985, 15:116-132.
[51]王哲.链条锅炉燃烧模糊预测控制系统[硕士学位论文].北京:北京科技大学, 2009.
[52]宋华,张洪钺,王行仁. T-S模糊故障树分析方法.控制与决策, 2005, 20(8):854-859.
[53]姚成玉,赵静一.基于T-S模型的液压系统故障树分析方法研究.中国机械工程, 2009,20(16):1913-1917.
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