面向重型数控机床的服役可靠性评估方法及增长技术研究
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摘要
重型数控机床主要用于大型零部件的加工，是国防军工、航天、船舶、能源、机械等国家重点企业的当家把关装备。由于重型数控机床是集成机械、电气、液压、和信息等多项技术的机电一体化产品，具有样本少、结构复杂、质量大、寿命长、故障多样等特点。传统的可靠性评估方法（基于失效数据）所需样本多，且对于可靠性高、寿命长的产品评估难度较大。因此仅仅采用基于失效的可靠性评估方法难以真实全面的反映重型数控机床可服役可靠性的变化情况。为解决这一问题，本文提出了基于“故障”“加工稳定性”“性能保持性”三个角度的不同的可靠性评估方法来全面的评估重型数控机床的服役可靠性，对重型数控机床提供具有指导意义的可靠性评估结果。在可靠性评估的基础上，对重型数控机床的可靠性增长技术进行了研究，提出了基于FMEA的维修策略优化方法和基于加工过程非线性动力学模型的多目标加工工艺参数优化方法，从而在维修和控制参数的角度对重型数控机床的服役可靠性进行了提高。
本文围绕基于失效、动态特性参数、性能劣化参数的三种可靠性评估方法，构建了重型数控机床服役可靠性评估体系，开展了基于“故障”“加工稳定性”和“性能保持性”的重型数控机床服役可靠性评估和可靠性增长技术研究，具体内容包括：
（1）给出了重型数控机床服役可靠性的定义，并从狭义可靠性、性能可靠性、维修可靠性、可用性四个角度建立了比较全面的重型数控机床的可靠性评估指标体系。从“故障”“加工稳定性”“性能保持性”三个不同的角度论述了重型数控机床可靠性的评估问题，并对三个不同角度出发的可靠性评估方法进行了国内外的研究概况分析。
（2）从“故障”的角度对重型数控机床服役可靠性进行分析，并基于重型数控机床失效数据进行可靠性评估，得到机床的各项可靠性指标。该评估方法通过绘制多台重型数控机床生产加工中的故障间隔时间及维修时间数据的概率密度函数及累计概率密度函数的散点图，通过对比排除法得到该类型重型数控机床的故障间隔时间和维修时间可能遵循的几类分布模型。通过K-S假设检验验证各假设分布的正确性并最终得到机床故障间隔时间和维修时间所满足的分布模型。由此可计算出重型数控机床的多项可靠性指标。
（3）从“加工稳定性”的角度对重型数控机床进行可靠性分析，通过基于机床动态特性参数的可靠性评估方法对机床的工艺可靠性进行了评估。该评估方法分析了机床-刀具-工件系统的振动特性并建立了机床加工过程的非线性动力学模型，通过激励试验和切削实验得到频率响应函数和切削力与进给速度之间的非线性关系，进而通过拟合和参数辨识得到机床的固有动态特性参数（固有频率、阻尼和刚度系数）和切削力模型参数。将各项参数代入到加工过程非线性动力学模型后求解得到机床的仿真振动曲线，用实际振动曲线对仿真曲线进行验证后，并由仿真曲线求得机床在指定工况下的工艺可靠性指标值。
（4）分析重型数控机床在使用过程中的性能劣化现象，从“性能保持性”的角度分析了对重型数控机床的可靠性，基于性能劣化数据进行机床的可靠性评估。采用隐马尔科夫链模型（HMM）描述机床的性能劣化过程与机床运行状态的隐含关系，根据机床的少样本多性能的特点，对标准隐马尔科夫链模型进行改进，得到可用于多性能多序列训练的马尔科夫链模型，经过对多台重型数控机床的多项关键性能参数数据的训练得到模型的参数估计值，然后基于此模型进一步计算得到该类重型数控机床的各状态概率变迁曲线和性能可靠度变迁曲线。
（5）分析维修对重型数控机床可靠性增长的影响，提出了基于模糊故障影响图的FMEA分析法，在FMEA分析结果的基础上充分考虑维修的成本、耗时等因素，针对不同的故障模式对可靠性的影响采用不同的维修策略，在保证有效提高可靠性的同时能更好的节约维修时间和维修成本。
（6）分析不同的加工工艺参数对加工稳定性的影响，提出优化加工工艺参数组合达到提高重型数控工艺可靠性的目的。同时，本文还将加工过程中的生产率、生产成本、加工尺寸精度以及表面粗糙度等因素引入到加工工艺参数的优化过程中，构建了基于加工过程非线性动力学模型的多目标加工工艺参数优化模型，并通过网格寻优算法对加工工艺参数的可行域进行寻优，由此得到更稳定、更快速、更低成本的加工工艺参数组合，尽可能的提高了机床的加工性能和加工稳定性。
最后，对全文进行了总结，并指出了进一步的研究方向。
The Heavy-duty CNC machine tools is mainly used for the manufacturing of large,extra large parts，is the key equipment of the national defense and military, aviation,aerospace, shipbuilding, energy, transportation, metallurgy, machinery and other key stateenterprises.The Heavy-duty CNC machine tools is a mechatronic products that integratesthemechanical, electrical, hydraulic, pneumatic, microelectronics and information andmany other technologies, withthe characters ofsmall sample size, complex structure, highweight, long life and various failure. Traditional reliability evaluation method (based onthe failure-time data) requireslarge sample, and is difficult to assess the high reliability,long life product. Therefore, merely using the reliability assessment method based onfailure-time is difficult to reflect the heavy-duty CNC machine tools‘real reliabilitycomprehensively. To solve this problem, this paper proposesthe three different reliabilityassessment methods with the angles of failure，‘processing stability‘and performanceretention‘to comprehensively assess the reliability of the heavy-duty CNC machine tools,to provide the guiding significance reliability assessment results. On the basis of reliabilityassessment, this paper researches for reliability growth technology of heavy-duty CNCmachine tools and proposes the maintenance strategy optimization method based onFMEA and the multi-objective optimization method of machining process paremetersbased on the nonlinear dynamic model, in order to improve the reliability of theHeavy-duty CNC machine tools from the point of view of maintenance and controlparameters.
This paper builds the reliability assessment system based on failure-time, dynamiccharacteristic parameters and performance parameters degradation, and carry out theresearch of running reliability assessment and reliability growth technology for theHeavy-duty CNC machine tools. The specific content including:
(1) This paper makes the definition ofrunning reliability of the heavy-duty CNCmachine tools, establishes the comprehensive reliability evaluation index system from theangle of narrow reliability, performance reliability, maintenance reliability and availability.The same time, due to the structure complexity and failure diversity of the heavy-dutyCNC machine tools, this paper discusses the reliability assessment problem from the theredifferent angle of the failure‘, processing stability‘and performance retention‘, and give the research reviews at home and abroad of the three reliability assessment methodsfocused on different angle.
(2) This paper firstly analyse the running reliability of the heavy-duty CNC machinetools focused on failure‘, assess the machine‘s reliability based on failure-time data andobtain the machine‘s reliability index. This assessment method draws the scatter plot ofthe probability density function and the cumulative probability density function ofmachine‘s time between failure and maintenance time. By comparing and excluding, somedistribution models will be chosen to meet the scatter plot of the probability densityfunction and the cumulative probability density function of machine‘s time betweenfailure and maintenance time. We can obtain the final distribution model and calculate allreliability indexes by K-S hypothesis testing.
(3) This paper sencondly analyse the machine reliability from the angle of processing stability‘, and assess the machine reliability by reliability assessment methodbased on dynamic characteristic parameters. The assessment method builds the nonlineardynamic model of the process according to vibration characteristics ofmachine-tool-workpiece system. Then, the frequency response function and cutting forcewill be obtained by experiment. The dynamic characteristic parameters and cutting forcemodel parameters could be obtained by fitting the frequency response function and thenonlinear relationship between the cutting force and the feed rate. The all dynamiccharacteristic parameters and cutting force model parameters will be taken into thenonlinear dynamic model and the model will be solved to obtain the machine simulationvibration curve. After verifying the nonlinear dynamic model by comparing with actualvibration curve, the process reliability index value at the specified operating conditionscould be obtained according to the mechine simulation vibration curve.
(4) This paper analys the performance degradation phenomenon in the runningprocess of the heavy-duty CNC machine tools, and assess the machine reliability from theangle of performance retention‘based on performance degradation data. The reliabilityassessment uses the hidden markov chain model to build the hidden relationship modelbetween performance degradation course and machine running state. Considering themachine‘s characteristics of small sample and multi-performance, this paper improve thestandard hidden markov chain model to obtain the hidden markov chain model that cantrain multi-sequence and multi-performance parameter. Based on the improved model, wecan obtain the probability transition curve of each state and reliability change curve.
(5) This paper analyses the affection of maintenance to reliability growth, and proposes the FMEA analysis based on fuzzy failure affection plot, and based on theanalysis result of FMEA, differet maintenance strategies will be used for different failuremodels after considering maintenance cost, time and other infactors. The maintenancestrategies optimization method could reduce effectively the maintenance cost and timebetter besides improve the machine‘s reliability.
(6) This paper analyses the impact of different process parameters on the processingstability and tries to improve the machine‘s process reliability by optimizing machiningprocess parameters combination. The same time, this paper takes the account ofproductivity, cost of production, dimensional accuracy and surface roughness factors intothe process of machining process parameter optimization, and build the multi-objectivemachining process parameter optimization model based on nonlinear dynamic model.Search the machining process parameter‘s feasible region by Grid Optimization Algorithmand obtain the more stable, more low-costand faster machining process parametercombinations, so as to impove machine‘s machining performance and stability.
Finally, a summary of the full article is proposed and the future research directions ispointed out.
本文围绕基于失效、动态特性参数、性能劣化参数的三种可靠性评估方法，构建了重型数控机床服役可靠性评估体系，开展了基于“故障”“加工稳定性”和“性能保持性”的重型数控机床服役可靠性评估和可靠性增长技术研究，具体内容包括：
（1）给出了重型数控机床服役可靠性的定义，并从狭义可靠性、性能可靠性、维修可靠性、可用性四个角度建立了比较全面的重型数控机床的可靠性评估指标体系。从“故障”“加工稳定性”“性能保持性”三个不同的角度论述了重型数控机床可靠性的评估问题，并对三个不同角度出发的可靠性评估方法进行了国内外的研究概况分析。
（2）从“故障”的角度对重型数控机床服役可靠性进行分析，并基于重型数控机床失效数据进行可靠性评估，得到机床的各项可靠性指标。该评估方法通过绘制多台重型数控机床生产加工中的故障间隔时间及维修时间数据的概率密度函数及累计概率密度函数的散点图，通过对比排除法得到该类型重型数控机床的故障间隔时间和维修时间可能遵循的几类分布模型。通过K-S假设检验验证各假设分布的正确性并最终得到机床故障间隔时间和维修时间所满足的分布模型。由此可计算出重型数控机床的多项可靠性指标。
（3）从“加工稳定性”的角度对重型数控机床进行可靠性分析，通过基于机床动态特性参数的可靠性评估方法对机床的工艺可靠性进行了评估。该评估方法分析了机床-刀具-工件系统的振动特性并建立了机床加工过程的非线性动力学模型，通过激励试验和切削实验得到频率响应函数和切削力与进给速度之间的非线性关系，进而通过拟合和参数辨识得到机床的固有动态特性参数（固有频率、阻尼和刚度系数）和切削力模型参数。将各项参数代入到加工过程非线性动力学模型后求解得到机床的仿真振动曲线，用实际振动曲线对仿真曲线进行验证后，并由仿真曲线求得机床在指定工况下的工艺可靠性指标值。
（4）分析重型数控机床在使用过程中的性能劣化现象，从“性能保持性”的角度分析了对重型数控机床的可靠性，基于性能劣化数据进行机床的可靠性评估。采用隐马尔科夫链模型（HMM）描述机床的性能劣化过程与机床运行状态的隐含关系，根据机床的少样本多性能的特点，对标准隐马尔科夫链模型进行改进，得到可用于多性能多序列训练的马尔科夫链模型，经过对多台重型数控机床的多项关键性能参数数据的训练得到模型的参数估计值，然后基于此模型进一步计算得到该类重型数控机床的各状态概率变迁曲线和性能可靠度变迁曲线。
（5）分析维修对重型数控机床可靠性增长的影响，提出了基于模糊故障影响图的FMEA分析法，在FMEA分析结果的基础上充分考虑维修的成本、耗时等因素，针对不同的故障模式对可靠性的影响采用不同的维修策略，在保证有效提高可靠性的同时能更好的节约维修时间和维修成本。
（6）分析不同的加工工艺参数对加工稳定性的影响，提出优化加工工艺参数组合达到提高重型数控工艺可靠性的目的。同时，本文还将加工过程中的生产率、生产成本、加工尺寸精度以及表面粗糙度等因素引入到加工工艺参数的优化过程中，构建了基于加工过程非线性动力学模型的多目标加工工艺参数优化模型，并通过网格寻优算法对加工工艺参数的可行域进行寻优，由此得到更稳定、更快速、更低成本的加工工艺参数组合，尽可能的提高了机床的加工性能和加工稳定性。
最后，对全文进行了总结，并指出了进一步的研究方向。
The Heavy-duty CNC machine tools is mainly used for the manufacturing of large,extra large parts，is the key equipment of the national defense and military, aviation,aerospace, shipbuilding, energy, transportation, metallurgy, machinery and other key stateenterprises.The Heavy-duty CNC machine tools is a mechatronic products that integratesthemechanical, electrical, hydraulic, pneumatic, microelectronics and information andmany other technologies, withthe characters ofsmall sample size, complex structure, highweight, long life and various failure. Traditional reliability evaluation method (based onthe failure-time data) requireslarge sample, and is difficult to assess the high reliability,long life product. Therefore, merely using the reliability assessment method based onfailure-time is difficult to reflect the heavy-duty CNC machine tools‘real reliabilitycomprehensively. To solve this problem, this paper proposesthe three different reliabilityassessment methods with the angles of failure，‘processing stability‘and performanceretention‘to comprehensively assess the reliability of the heavy-duty CNC machine tools,to provide the guiding significance reliability assessment results. On the basis of reliabilityassessment, this paper researches for reliability growth technology of heavy-duty CNCmachine tools and proposes the maintenance strategy optimization method based onFMEA and the multi-objective optimization method of machining process paremetersbased on the nonlinear dynamic model, in order to improve the reliability of theHeavy-duty CNC machine tools from the point of view of maintenance and controlparameters.
This paper builds the reliability assessment system based on failure-time, dynamiccharacteristic parameters and performance parameters degradation, and carry out theresearch of running reliability assessment and reliability growth technology for theHeavy-duty CNC machine tools. The specific content including:
(1) This paper makes the definition ofrunning reliability of the heavy-duty CNCmachine tools, establishes the comprehensive reliability evaluation index system from theangle of narrow reliability, performance reliability, maintenance reliability and availability.The same time, due to the structure complexity and failure diversity of the heavy-dutyCNC machine tools, this paper discusses the reliability assessment problem from the theredifferent angle of the failure‘, processing stability‘and performance retention‘, and give the research reviews at home and abroad of the three reliability assessment methodsfocused on different angle.
(2) This paper firstly analyse the running reliability of the heavy-duty CNC machinetools focused on failure‘, assess the machine‘s reliability based on failure-time data andobtain the machine‘s reliability index. This assessment method draws the scatter plot ofthe probability density function and the cumulative probability density function ofmachine‘s time between failure and maintenance time. By comparing and excluding, somedistribution models will be chosen to meet the scatter plot of the probability densityfunction and the cumulative probability density function of machine‘s time betweenfailure and maintenance time. We can obtain the final distribution model and calculate allreliability indexes by K-S hypothesis testing.
(3) This paper sencondly analyse the machine reliability from the angle of processing stability‘, and assess the machine reliability by reliability assessment methodbased on dynamic characteristic parameters. The assessment method builds the nonlineardynamic model of the process according to vibration characteristics ofmachine-tool-workpiece system. Then, the frequency response function and cutting forcewill be obtained by experiment. The dynamic characteristic parameters and cutting forcemodel parameters could be obtained by fitting the frequency response function and thenonlinear relationship between the cutting force and the feed rate. The all dynamiccharacteristic parameters and cutting force model parameters will be taken into thenonlinear dynamic model and the model will be solved to obtain the machine simulationvibration curve. After verifying the nonlinear dynamic model by comparing with actualvibration curve, the process reliability index value at the specified operating conditionscould be obtained according to the mechine simulation vibration curve.
(4) This paper analys the performance degradation phenomenon in the runningprocess of the heavy-duty CNC machine tools, and assess the machine reliability from theangle of performance retention‘based on performance degradation data. The reliabilityassessment uses the hidden markov chain model to build the hidden relationship modelbetween performance degradation course and machine running state. Considering themachine‘s characteristics of small sample and multi-performance, this paper improve thestandard hidden markov chain model to obtain the hidden markov chain model that cantrain multi-sequence and multi-performance parameter. Based on the improved model, wecan obtain the probability transition curve of each state and reliability change curve.
(5) This paper analyses the affection of maintenance to reliability growth, and proposes the FMEA analysis based on fuzzy failure affection plot, and based on theanalysis result of FMEA, differet maintenance strategies will be used for different failuremodels after considering maintenance cost, time and other infactors. The maintenancestrategies optimization method could reduce effectively the maintenance cost and timebetter besides improve the machine‘s reliability.
(6) This paper analyses the impact of different process parameters on the processingstability and tries to improve the machine‘s process reliability by optimizing machiningprocess parameters combination. The same time, this paper takes the account ofproductivity, cost of production, dimensional accuracy and surface roughness factors intothe process of machining process parameter optimization, and build the multi-objectivemachining process parameter optimization model based on nonlinear dynamic model.Search the machining process parameter‘s feasible region by Grid Optimization Algorithmand obtain the more stable, more low-costand faster machining process parametercombinations, so as to impove machine‘s machining performance and stability.
Finally, a summary of the full article is proposed and the future research directions ispointed out.
引文
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[50] Rausand M. Reliability centered maintenance. Reliability Engineering&SystemSafety,1998,60(2):121-132.
[51] Blischke W.R., Murthy D.N.P., Reliability: modeling, prediction, and optimization(2000). New York: Wiley.
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[54] Yang K., Xue J., Continuous state reliability analysis. Annual Reliability andMaintainability Symposium.1996:251-257.
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[58] Heng A., Zhang S., Tan A.C.C., Mathew J., Rotating machinery prognostics: Stateof the art, challenges andopportunities. Mechanical Systems and SignalProcessing, In Press, Corrected Proof.2008.
[59] Vachtsevanos G.J., Lewis F.L., Roemer M., Hess A., Wu B., Intelligent faultdiagnosis and prognosis forengineering systems. Hoboken, NJ: Wiley.2006.
[60] Zhang L., Li X., Yu J., A review of fault prognostics in condition basedmaintenance. Sixth InternationalSymposium on Instrumentation and ControlTechnology: Signal Analysis, Measurement Theory, Photo-ElectronicTechnology,and Artificial Intelligence China.2006:1-6.
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[63] Kothamasu R., Huang S., VerDuin W., System health monitoring and prognostics—a review of currentparadigms and practices. The International Journal ofAdvanced Manufacturing Technology,2006,28(9):1012-1024.
[64] Katipamula S., Brambley M.R., Methods for fault detection, diagnostics, andprognostics for building systems—areview, part I. International Journal ofHVAC&R Research,2005,11(1):3-25.
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[68] Weibull W., A statistical distribution function of wide applicability. Journal ofApplied Mechanics,1951,18(3):293-297.
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