摘要
维修是为了保持和恢复系统良好工作状态所进行的一切活动。维修决策研究的目的是为系统安排合理的维修计划,以用最少的经济代价、时间、资源以及最高的修复率,使系统经常处于完好状态,提高可用性和可靠性,降低退化速度,延长使用寿命,保障使用中的安全性和环境保护等。维修决策的研究内容主要包括维修方式的决策以及各维修方式下如何为系统安排合理的维修计划。本文针对当前维修方式和视情维修决策中存在的一些问题,结合离心压缩机转子系统,对以下几个方面进行了探索和研究:
(1)未知权值和混合数据下维修方式决策的研究。将决策者提供的用定性语言描述的属性间的成对比较矩阵转化为模糊数矩阵,采用模糊偏好规划方法求取各属性符合决策者偏好的清晰(crisp)权值。为了解决混合数据问题,提出了基于随机优势和模糊数质心距的ELECTRE III方法。这一方法创建基于模糊数质心距的局部和谐指数和非和谐指数,用于解决任意两个维修方式在模糊评价下的比较问题,并与基于随机优势的局部和谐指数和非和谐指数及ELECTRE III方法相结合,解决混合数据问题。将上述方法应用到离心压缩机转子系统的维修方式决策中,结果表明,提出的方法能为系统在未知权值和混合数据下选择合理的维修方式。
(2)离心压缩机转子系统状态评估的研究。采用基于模型的处理方法来估计转子的不平衡量、弯曲量及不对中程度,为了降低噪声对估计精度的影响,提出了基于改进的EMD预处理方法,用有限元分析来论证其有效性;提出基于轴向力的离心压缩机级密封状态的评估方法,该方法采用BP神经网络建立级密封状态和轴向力的关系模型并将训练好的BP神经网络模型用于估计级密封状态,采用FLUENT软件计算不同级密封状态下的轴向力,以验证方法的有效性。结果表明,基于改进的EMD预处理方法和基于模型的处理方法相结合能比较准确地识别出转子系统的不平衡量、弯曲量和不对中程度;基于轴向力的离心压缩机级密封状态的评估方法能较为准确地估计出级密封的状态。
(3)连续完全监测的多退化状态变量系统的视情维修决策研究。采用不同参数的平稳Gamma过程描述各退化状态变量,给出平稳Gamma过程单参数的共轭先验分布并进行了证明;推导了单个退化状态变量下预防性维修的期望间隔时间模型,由此得出系统预防性维修的期望间隔时间;根据有效年龄模型(effective age model)的思想建立了不完全预防性维修对系统状态的影响模型;建立了单位时间的期望运行成本模型和平均可用度模型,在此基础上,根据机会维修决策模型的思想,构建了连续完全监测的多退化状态变量系统的视情维修决策模型,并提出改进的理想点法对其进行求解。将提出的模型应用到离心压缩机转子系统的状态分别由不平衡量和由不平衡量、级密封状态及弯曲量决定下的视情维修决策中,数值分析结果表明,提出的模型可以解决连续完全监测的多退化状态变量系统的视情维修决策问题。
(4)遭受突然失效和多类退化失效系统的视情维修决策研究。使用不同参数的平稳Gamma过程描述各退化状态变量,推导出单个退化状态变量系统的可靠度计算公式,并采用贝叶斯估计方法实现可靠度中参数的实时估计,其中该方法还考虑了监测噪声的影响。采用两参数weibull分布描述系统突然失效时间的分布,使用贝叶斯估计方法实现可靠度中参数的实时估计。建立了系统同时遭受突然失效和多类退化失效时的可靠度模型,将可靠度作为表征系统状态的指标。创建系统无失效时的预防性维修间隔时间模型以及一次循环内的期望运行时间、停机时间、单位时间的期望运行成本模型,在此基础上,构建了系统同时遭受突然失效和多类退化失效下的视情维修决策模型。将该方法应用到离心压缩机转子系统同时遭受由于不平衡量增大导致的退化失效和轴或者叶轮出现裂纹而导致的突然失效下的视情维修决策中,算例分析结果表明,提出的系统同时遭受突然失效和多类退化失效时的视情维修决策模型是有效的。
本文针对当前维修方式和视情维修决策中存在的一些问题,结合离心压缩机转子系统这一对象,提出了可行的解决方法,为维修决策的深入研究及其在离心压缩机转子系统甚至其他系统中的应用提供一定的参考。
Maintenance is the performed actions to keep and restore the system in a well condition. The objective of maintenance decision making (MDM) is to scheme the optimal maintenance plan for a system to make the system in a good condition usually, improve system reliability and availability, decrease the deterioration rate, prolong the service life, guarantee the safety as much as possible during system operating, protect the environment and so on under the condition of the minimization of the spent cost, time and other resource and the maximization of the restoration ratio. The research content of MDM consists of the maintenance policy decision making and making the optimal maintenance plan for a system under a certain maintenance policy. In this dissertation, aiming at some problems of the decision making of maintenance policy and condition-based maintenance which have not been solved and are combined with the rotor system of centrifugal compressor, the following contents are explored:
(1) Study on maintenance policy decision making with mix data and unknown weight of every attribute. The qualitative pairwise compassion matrix among attributes which is presented by decision-makers is transformed into the fuzzy number matrix before the fuzzy preference programming method is employed to calculate the crisp weights of all attributes. To solve the ploblem of mix data, the ELECTRE III based stochastic dominance and the distance between the centroid point of a fuzzy number and coordinate origin (DCPFNCO) is proposed. The approach constructs the local harmonious and non-harmonious index (LHI and LNHI) based on DCPFNCO firstly in order to solve the problem of the comparision of any two maintenance polices under fuzzy evaluation, and they are combined with LHI and LNHI based on stochastic dominance and ELECTRE III to solve the ploblem of mix data. The proposed approach is applied to maintenance policy decision making of the rotor system of centrifugal compressor. The results of the numerical example show that the optimal maintenance policy for a system could be determined by the proposed approach.
(2) Study on condition assessement of the rotor system of centrifugal compressor. The model-based approach is employed to assess the unbalance quantity, the degree of misalignment and the quantity of bending deformation of the rotor system; the preprocessing approach based the improved EMD is presented to reduce the effect of noise on the assessement accuracy; then, finite element analysis is used to verify the two approaches.The condition assessment approach of the stage seal of centrifugal compressor based on the axial thrust is proposed, where the BP neural network is applied to express the relationship between the axial thrust and the stage seal condition and the trained BP neural network is used to assess the stage seal condition; the axial thrusts are calculated by FLUENT under the different condition of the stage seal to verify the proposed approach. According to the results of the numerical examples, it could be seen that the unbalance quantity, the degree of misalignment and the quantity of bending deformation of the rotor system could be assessed accurately by the preprocessing approach based the improved EMD and the model-based approach; the stage seal condition could be estimated exactly by the condition assessment approach of the stage seal of centrifugal compressor based on the axial thrust.
(3) Study on condition-based maintenance optimization for the system of which the condition is determined by multi-deterioration condition variables monitored continuously and perfectly. Suppose each deterioration condition variable follow a stationary Gamma process with two certain parameters which are estimated by Bayesian estimation method. The conjugate prior distribution of single parameter of the stationary Gamma process could be obtained and is proved in this section. Then, the expected time interval model of the preventive maintenance of the system whose condition is determined by only one deterioration condition variable is derived and that of the considered system is given subsequently. The effect of the imperfect preventive maintenance on the system condition is formulated according to the idea of the effective age model and the expected restoration time period model of the imperfect preventive maintenance in some literatures is used. The expected operation cost per unit time and the expected availability of the considered system are modeled. On these bases, the condition-based maintenance optimization model for the system whose condition is determined by multi-deterioration condition variables monitored continuously and perfectly is formulated and solved by the improved ideal point method which is proposed in this dissertation. The proposed approach is applied to two cases that the rotor system of centrifugal compressor of which the condition is determined only by unbalance quantity and by unbalance quantity, stage seal condition and the quantity of bending deformation of the shaft, respectively. The results of the numerical examples show that the proposed maintenance optimization model accords with practical engineering and could solve the problem of condition-based MDM for the system of which the condition is determined by multi-deterioration condition variables monitored continuously and perfectly.
(4) Study on condition-based maintenance optimization for the system subject to sudden failure and multiple deterioration failure simultaneously. Each deterioration condition variable is assumed to follow a stationary Gamma process with two certain parameters; then, the reliability of the system whose condition is determined by only one deterioration condition variable is derived on the basis of the reliability definition, whose parameter is estimated real-timely by the Bayesian estimation method. Suppose the sudden failure time follow the Weibull distribution with two parameters; then, the reliability of the system subject to only the sudden failure is modeled whose parameters is estimated real-timely by Bayesian estimation method with the conjugate prior distribution of two parameters. Subsequently, the considered system reliability is formulated on the basis of the above two reliability models. It is used for the index of the condition of the system. The models of the interval between two preventive maintenances under the condition without sudden failure, the expected uptime and downtime of the system in a cycle and the expected operational cost per unit time are modeled respectively. On these bases, the condition-based maintenance optimization model for the system undergoing the sudden failure and multi-deterioration failure simultaneously is formulated. The proposed approach is applied to the condition-based MDM of the rotor system of centrifugal compressore which suffer from sudden failure due to occurrence of the crack of the shaft or impeller and deterioration failure due to increase of unbalance quantity. The results of the numerical examples show that the presented condition-based maintenance optimization model for the system undergoing the sudden failure and multi-deterioration failure simultaneously is effective.
To sum up, some feasible and effective approaches to solving the not solved problem of decision making of maintenance policy and condition-based maitiance are proposed in this dissertation and they may provides some references for the deep research on MDM and the application of MDM to the rotor system of centrifugal compressor or other system.
引文
1陈学楚.维修基础理论.科学出版社, 1998: 1-5
2 A. H. Christer. Developments in Delay Time Analysis for Modelling Plant Malntenance. Journal of the Operational Research Soeiety, 1999, 50: 1111,1120-1137
3王凌.维修决策模型和方法的理论研究与应用研究.浙江大学博士论文. 2007: 1-20
4 M. Bevilacqua, M. Braglia. The Analytic Hierarchy Process Applied to Maintenance Strategy Selection. Reliability Engineering and System Safety, 2000, 70: 71-83.
5 M. W. Lewis, L. Steinberg. Maintenanee of Mobile Mine Equipment in the Information Age. Journa of Quality in Maintenanee Engineering, 2001, 7(4): 264-274.
6 R. K. Mobley.An Introduction to Predictive maintenance,second edition. Elsevier seience, 2002: 23-247
7 U. Graber. Advanced Maintenance Strategies for Power Plant Operators- introducing Inter-plant Life Cycle Management. International Journal of PressureVessels and Piping, 2004, 81: 861- 865
8 J. S. Tan , M. A. Krarner. A General Framework for Preventive Maintenance Optimization in Chemical Proeess Operations. Computers and Chemical Engineering, 1997, 21(12): 1451-1469.
9陈冠国.机械设备维修.机械工业出版社, 2005: 78-93
10 S. Luce. Choice Criteria in Conditional Preventive Maintenance. Mechanical Systems and Signal Processing, 1999, 13(1): 163-168.
11 S. Okumura, N. Okino. A Maintenance Policy Selection Method for a Critical Single-unit Item in Each Workstation Composing a FMS with CBM Optimization. International Journal of COMADEM, 2003, 6(2): 3-9.
12 F. Azadivar, V. Shu. Maintenance Policy Selection for JIT Production Systems. International Journal of Production Research, 1999, 37 (16): 3725-3738.
13 M. Bevilacqua, M. Braglia. The Analytic Hierarchy Process Applied toMaintenance Strategy Selection. Reliability Engineering and System Safety, 2000, 70: 71-83.
14常建娥,蒋太立.模糊综合评判在设备维修决策中的应用.组合机床与自动化加工技术, 2006, (3): 26-28.
15 L. Wang, J. Chu, J. Wu. Selection of Optimum Maintenance Strategies Based on a Fuzzy Analytic Hierarchy Process. International Journal of Production Economics, 2007, 107: 151-163
16 B. Al-Najjar, I. Alsyouf. Selecting the Most Efficient Maintenance Approach Using Fuzzy Multiple Criteria Decision Making. International Journal of Production Economics, 2003, 84: 85-100.
17 R. K. Sharma, D. Kumar, P. Kumar. FLM to Select Suitable Maintenance Strategy in Process Industries Using MISO Model. Journal of Quality in Maintenance Engineering, 2005, 11(4): 359–374.
18 C. K. Mechefske, Z. Wang. Using Fuzzy Linguistics to Select Optimum Maintenance and Condition Monitoring Strategies. Mechanical Systems and Signal Processing, 2003, 17(2): 305-316
19 C. G. L. H. Fe′lix, J. R. C. Jose′. Maintenance Strategy Based on a Multicriterion Classification of Equipments. Reliability Engineering and System Safety , 2006, 91: 444–451
20 H. Z. Wang. A Survey of Maintenance Policies of Deteriorating Systems. European Journal of Operational Research, 2002, 139: 469–489
21 R. W. Drinkwater, N. V. J. Hastings. An Economic Replacement Model. Operational Research Quarterly, 1967, 18: 121-138
22 T. Nakagawa, S. Osaki. The Optimum Repair Limit Replacement Policies. Operational Research Quarterly, 1974, 25: 311-317
23 T. Dohi, N. Matsushima, N. Kaio, S. Osaki. Nonparametric Repair-limit Replacement Policies with Imperfect Repair. European Journal of Operational Research, 1997, 96 (2): 260-273
24 H. Koshimae, T. Dohi, N. Kaio. Graphical Statistical Approach to Repair Limit Replacement Problem. Journal of the Operations Research Society of Japan, 1996, 39(2): 230-246
25 H. Morimura, H. Makabe. A New Policy for Preventive Maintenance. Journal of the Operations Research Society of Japan, 1963, 5: 110-124
26 H. Morimura. On Some Preventive Maintenance Policies for IFR. Journal of the Operations Research Society of Japan, 1970, 12(3): 94–124.
27 E. J. Muth. An Optimal Decision Rule for Repair vs. Replacement. IEEE Transactions on Reliability, 1977, 26(3): 179-181
28 V. Makis, A. K. S. Jardine. Optimal Replacement Policy for a General Model with Imperfect Repair. Journal of the Operational Research Society, 1992, 43(2): 111-120.
29 R. E. Barlow, L. C. Hunter. Optimum Preventive Maintenance Policies. Operations Research, 1960, 8:90–100.
30 H. Pham, H. Wang. Imperfect Maintenance. European Journal of operational Researeh, 1996, 94: 425-438.
31 C. Valdez-Flores, R. M. Feldman. A Survey of Preventive Maintenance Models for Stochastically Deterioration Single-unit System. Naval research logitics, 1989, 36(4): 419-446.
32 H. Wang, H. Pham. Some Maintenance Models and Availability with Imperfect Maintenance in Production Systems. Annals of Operations Research, 1999, 91: 305-318.
33陈学楚.现代维修理论.国防工业出版社, 2003: 1-100
34 M. Berg, B. Epstein. A Modified Block Replacement Policy. Naval Research Logistics, 1976, 23: 15-24.
35 K. S. Smidt-Destombesa, M. C. Van Der Heijden, A. Van Harten. Availability of k-out-of-N Systems under Block Replacement Sharing Limited Spares and Repair Capacity. International Journal of Production Economics, 2007, 107: 404-421
36 V. A. Vladimir. Asymptotic Analysis of Stochastic Block Replacement Policies for Multicomponent Systems in a Markov Environment. Operations Research Letters, 2005, 33: 26-34
37 S. Shey-Huei, S. W. Griffith. Extended Block Replacement Policy with Shock Models and Used Items. European Journal of Operational Research, 2002, 140: 50-60
38 X. Liu, V. Makis, A. K. S. Jardine. A replacement model with overhauls and repairs. Naval Research Logistics, 1995, 42: 1063-1079.
39 R. E. Barlow, F. Proshan. Mathematical Theory of Reliability. Wiley, 1965: 5-300
40 T. Nakagawa. Periodic and Sequential Preventive Maintenance Policies. Journal of Applied Probability, 1986, 23(2): 536-542.
41 T. Nakagawa. Sequential Imperfect Preventive Maintenance Policies. IEEE Transactions on Reliability, 1988, 37(3): 295-298.
42 W. J. Chen. Minimizing Number of Tardy Jobs on a Single Machine Subject to Periodic Maintenance. Omega, 2009, 37: 591-599
43 D. H. Xu, K. B. Sun, H. X. Li. Parallel Machine Scheduling with Almost Periodic Maintenance and Non-preemptive Jobs to Minimize Makespan. Computers & Operations Research, 2008, 35: 1344-1349
44 M. Ji, Y. He, T. C. E. Cheng. Single-machine Scheduling with Periodic Maintenance to Minimize Makespan. Computers & Operations Research, 2007, 34: 1764-1770
45 A. Grigoriev, J. Van De Klundert, F. C. R. Spieksma. Modeling and Solving the Periodic Maintenance Problem. European Journal of Operational Research, 2006, 172: 783-797
46 C. H. Lie, Y. H. Chun. An Algorithm for Preventive Maintenance Policy. IEEE Transactions on Reliability, 1986, 35 (1), 71-75
47 D. M. Frangopol, M. J. Kallen, J. M. Van Noortwijk. Probabilistie Models for Life-cycle Performance of Deteriorating Structures Review and Future Direetions. Progress in Structural Engineering and Materials, 2004(6): 197-212
48 X. J. Zhou, L. F. Xi, J. Lee. Reliability-centered Predictive Maintenance Scheduling for a Continuously Monitored System Subject to Degradation. Reliability Engineering and System Safety, 2007, 92: 530-534
49 J. A. M. Hontelez, H. H. Burger, D. J. D. Wijnmalen. Optimum Condition-based Maintenance Policies for Deteriorating Systems with Partial Information. Reliability Engineering and System Safety, 1996, 51: 267-274
50 K. S. Park.Optimal Continuous-wear Limit Replacement Under Periodic Inspections. IEEE Transaction on Reliability,1988, 37(1): 97-102
51 M. J. Kallen, J. M. Van Noortwijk. Optimal Maintenance Decisions under Imperfect Inspection. Reliability Engineering and System Safety, 2005, 90:177–185
52 R. H. Yeh. State-age-dependent Maintenance Policies for Deteriorating Systems with Erlang Sojourn Time Distributions. Reliability Engineering and System Safety, 1997, 58: 55–60
53 C. Be′renguer, A. Grall, B. Castanier. Simulation and Evaluation of Condition-based Maintenance Policies for Multi-component Continuous-state Deteriorating Systems. Proceedings of the Foresight and Precaution Conference, Edinburgh, 2000: 275–282
54 A. Grall, C. Be′renguer, C. Chu. Optimal Dynamic Inspection/replacement Planning in Condition-based Maintenance. Proceedings of the European Safety and Reliability Conference—ESREL’98, Trondheim, 1998: 381-388
55 A. Grall, L. Dieulle, C. Be′renguer. Continuous-time Predictive-maintenance Scheduling for a Deteriorating System. IEEE Transaction on Reliability, 2002, 51: 141-150
56 A. Grall, C. Bearenguer, L. Dieulle. A Condition-based Maintenance Policy for Stochastically Deteriorating Systems. Reliability Engineering and System Safety, 2002, 76: 167-180
57 M. J. Kallen, J. M. Van Noortwijk. Optimal Periodic Inspection of a Deterioration Process with Sequential Condition States. International Journal of Pressure Vessels and Piping, 2006, 83: 249–255
58 L. Dieulle, C. Beerenguer, A. Grall, M. Roussignol. Sequential Condition-based Maintenances Cheduling for a Deteriorating System. European Journal of Operational Research, 2003,150: 451-461
59 M. P. Kaminskiy, V. V. Krivtsov. A Simple Procedure for Bayesian Estimation of the Weibull Distribution. IEEE Transactions on Reliability, 2005, 54(4): 612-616
60 B. Saassouh, L. Dieulle, A. Grall. Online Maintenance Policy for a Deteriorating System with Random Change of Mode. Reliability Engineering and System Safety 2007; 92: 1677-1685
61 H. T. Liao, E. A. Elsayed, L. Y. Chan. Maintenance of Continuously Monitored Degrading Systems. European Journal of Operational Research, 2006, 175: 821-835
62 M. S. Moustafa, E. Y. A. Maksoud, S. Sadek. Optimal Major and MinimalMaintenance Policies for Deteriorating Systems. Reliability Engineering andSystem Safety, 2004, 83: 363–368
63 R. C. Vergin, M. Scriabin. Maintenance Scheduling for Multi-component Equipment. AIIE Transactions, 1977, 9: 297-305
64 S. H. Sheu, J. P. Jhang. A Generalized Group Maintenance Policy. European Journal of Operational Research, 1996, 96: 232-247
65 R. E. Wildeman, R. Dekker, A. C. J. M. Smi. A Dynamic Policy for Grouping Maintenance Activities. European Journal of Operational Research, 1997, 99: 530–551
66 M. Berg. Optimal Replacement Policies for Two-unit Machines with Increasing Running Costs-I. Stochastic Processes and Applications, 1976, 5: 89-106.
67 M. Berg. General Trigger-off Replacement Procedures for Two-unit Systems. Naval Research Logistics, 1978, 25: 15-29
68 H. Pham, H. Wang. Optimal (τ,T ) Opportunistic Maintenance of a k-out-of-n: G System with Imperfect PM and Partial Failure. Naval Research Logistics, 2000, 47: 223-239
69 L. R. Cui, H.J. Li. Opportunistic maintenance for multi-component shock models. Mathematical Methods of Operations Research, 2006, 63: 493-511
70 Y. T. Tsai, K. S. Wang, L. C. Tsai. A Study of Availability-centered Preventive Maintenance for Multi-component Systems. Reliability Engineering and System Safety, 2004, 84: 261–270
71 B. Castanier, A. Grall, C. Be′renguer. A Condition-based Maintenance Policy with Non-periodic Inspections for a Two-unit Series System. Reliability Engineering and System Safety, 2005, 87: 109–120
72雷涛.设备状态的模糊综合评估.燕山大学学报, 1996, 20(2): 182-185
73徐凌宇,杜庆东,赵海.基于嵌入式多信息源联合评价的方法及应用.东北大学学报(自然科学版), 2000.4, 21(4): 119-121.
74 Y. M. Wang, T. M. S. Elhag. Evidential Reasoning Approach for Bridge Condition Assessment. Expert Systems with Applications, Expert Systems with Applications, 2008, 34: 689–699
75金家善,严华,谭猛泉,孙丰瑞.舰用设备技术状态综合评估的结构完整性模型.船舶工程, 2003,25(6): 64-67.
76张晓东,胡明,张振中.船舶机电设备评估指标研究.船舶工程, 2005, 27(2): 45-48.
77 R. Jiang, A. K. S. Jardine. Health State Evaluation of an Item: A General Framework and Graphical Representation. Reliability Engineering and System Safety, 2008, 93(1): 89-99
78吴国华,丁光正,郭溪泉.设备的状态监测与工况评估.山西机械, 1999, (2): 11-13
79 J. M. W. Brownjohn, P. Q . Xia, H. Hao, Y. Xia. Civil Structure Condition Assessment by FE Model Updating: Methodology and Case Studies. Finite Elements in Analysis and Design, 2001, 37: 761-775.
80辛学忠,苏木标,陈树礼,夏禾.大跨度铁路桥梁健康状态评估的统计对比诊断方法研究.铁道学报, 2006, 28(2): 116-121.
81 X. Zhang, E. Gockenbach. Assessment of the Actual Condition of the Electrical Components in Medium-Voltage Networks. IEEE Transactions on reliability, 2006, 55(2):361-368
82国蓉,程光旭,王毅,郑宝祥,王会民.基于可拓模糊理论的Texaco煤气化运行状况评估方法研究.高校化学工程学报, 2005, 19(1): 77-83
83金家善,谭猛泉,孙丰瑞.基于贴近度的机械设备技术状态综合评估方法.海军工程大学学报, 2003,15(2):1-6.
84耿俊豹,黄树红,金家善,刘伟.基于任务剖面的复杂系统状态综合评估方法.华中科技大学学报(自然科学版), 2006, 34(1): 27-29.
85崔厚玺,张来斌,王朝晖,陈朝晖,黄洪俊.基于多参数评判技术的轴承状态评估研究.中国设备工程, 2006,增1: 31-33.
86陈刚,李冰,陈非,黄树红.大型火电机组引风机的状态检修.华中科技大学学报(自然科学版), 2007, 35(1): 63-66.
87李凌均,韩捷,郝伟,董辛,何正嘉.支持向量数据描述用于机械设备状态评估研究.机械科学与技术, 2005.12, 24(12):1426-1429.
88 L. Zhang, Q. X. Cao, J. Lee, F. L. Lewis. PCA-CMAC Based Machine Performance Degradation Assessment. Journal of Southeast University (English Edition), 2005, 21(3): 299-303
89 G. DIANA. Diagnostics of Rotating Machines in Power Plants. Springer Verlag Wien , 1994: 37-47
90 L. S. Qu, Y. D. Shen. Orbit Complexity: A New Criterion for Evaluating theDynamic Quality of Rotor Systems. Journal of Mechanical Engineering Science, 1993, 207: 325-334
91杨文献,徐光华,屈梁生.时域信号复杂度指标的建立及其在机械故障诊断技术中的应用.中国机械工程,1999,10 (3) :307～310
92杨文献,姜节胜.大型回转机组变工况运行状态快速评估方法研究.中国机械工程, 2001, 12(10): 1173-1175.
93杨文献.大机组起停车状态在线监测方法研究.西安交通大学学报, 1999, 33(1): 100-104.
94张金萍,刘国贤,袁泉,杨希成,郑明涛.变电设备健康状态评估系统的设计与实现.现代电力, 2004, 21(4): 45-48.
95祝晓燕,杨敬娜.基于AHP-FUZZY方法的火电厂设备状态分级评价.华北电力大学学报, 2007, 34(1): 132-136.
96彭欣.油化技术监督在变压器状态评估中的应用.电力设备, 2006, 6(10): 58-60
97 A. M. Robert, S. K. Sinh. Condition Assessment of Underground Sewer Pipes Using a Modified Digital Image Processing Paradigm. Trenchless Technology Research, 1999, 14(2): 29-37.
98 S. W. Park, Y. S. Shin, Y. S. Oh, S. R. Ahn. Guideline on Condition Assessment of Existing Old Railway Tunnels. Tunnelling and Underground Space Technology , 2006, 21: 329–330.
99 I. L. Hosier, A. S. Vaughan, S. J. Sutton. A Novel Optical Diagnostic Tool for Condition Assessment of Insulation Oils. Conference Record of the 2006 IEEE International Symposium on Electrical Insulation, Toronto, 2006: 77-80.
100 G. R. Soltani, E. David. Condition Assessment of Rotating Machine Winding Insulation by Analysis of Charging and Discharging Currents. Conference Record of the 2006 IEEE International Symposium on Electrical Insulation, Toronto, 2006: 336-339.
101郭磊,陈进.小波包熵在设备性能退化评估中的应用.机械科学与技术, 2008, 27(9): 4020-4023
102董玉亮.发电设备运行与维修决策支持系统研究.华北电力大学博士论文, 2005: 1-20
103张秀斌.视情维修决策模型及应用研究.国防科技大学博士论文, 2003: 1-22
104梁剑.基于成本优化饿民用航空发动机视情维修决策研究.南京航空航天大学博士论文, 2004: 1-27
105 P. J. M. Van Laarhoven, W. Pedrycz. Fuzzy Extension for Saaty’s Priority Theory. Fuzzy Sets and Systems, 1983, 11: 229-241
106 M. Wagenknecht, K. Hartmann. On Fuzzy Rank Ordering in Polyoptimisation. Fuzzy Sets and Systems, 1983, 11: 253-264
107 J. Buckley. Fuzzy Hierarchical Analysis. Fuzzy Sets and System, 1985, 17: 233-247
108 D. A. Chang. Application of the Extent Analysis Method on Fuzzy AHP. European Journal of Operational Research, 1996, 95: 649-655
109 G. Munda,P. Nijkamp, P. Rietveld. Qualitative Multicriteria Methods for Fuzzy Evaluation Problems: An Illustration of Economic-ecological Evaluation. European Journal of Operational Research, 1995, 82:79-97
110 Z. Kazimierz. Rough Approximation of a Preference Relationby a Multi-attribute Dominance for Deterministic, Stochastic and Fuzzy Decision Problems. European Journal of Operational Research, 2004, 159:196-206
111 M. Nowak. Preference and Veto Thresholds in Multicriteria Analysis Based on Stochastic Dominance. European Journal of Operational Research, 2004, 158: 339-350
112徐玖平,吴巍.多属性决策的理论与方法.清华大学出版社, 2006: 1-200
113 L. Mikhailov. Deriving priorities from fuzzy pairwise comparison judgements. Fuzzy Sets and Systems, 2003, (134):365-385
114 M. Nowak. Preference and Veto Thresholds in Multicriteria Analysis Based on Stochastic Dominance. European Journal of Operational Research, 2004, 158:339-350
115 C. H. CHENG. A New Approach for Ranking Fuzzy Numbers by Distance Method. Fuzzy Sets and Systems, 1998, 95:307-317
116 W. Klingenberg, T. W. de Boer. Condition-based maintenance in punching/ blanking of sheet metal. International Journal of Machine Tools & Manufacture, 2008, 48: 589-598
117张庆涛.离心压缩机智能故障诊断方法研究.大庆石油学院硕士学位论文. 2006: 7-9
118胡万明.氯气离心式压缩机振动状态监测与故障诊断分析.浙江工业大学硕士学位论文. 2007:30-49
119蒋其友.人工智能理论与技术的研究及其在大型离心压缩机故障诊断中的应用.北京化工大学博士学位论文. 1993: 34-40
120 S. V. Nalinaksh, D. Satishkumar. Artificial Neural Network Design for Fault Identification in a Rotor-bearing System. Mechanism and Machine Theory, 2001, 36: 157-175
121 Y. P. Zhang, S. H. Huang, J. H. Hou, T. Shen, W. Liu. Continuous wavelet grey moment approach for vibration analysis of rotating machinery. Mechanical Systems and Signal Processing, 2006, 20: 1202–1220
122 J. W. Zhang, N. H. Zhu, L. Yang, Q. Yao, Q. Lu. A fault diagnosis approach for broken rotor bars based on EMD and envelope analysis. Journal of China University of Mining & Technology. 2007, 17(2): 0205-0209
123向玲,朱永利,唐贵基. HHT方法在转子振动故障诊断中的应用.中国电机工程学报, 2007, 27(35): 84-89
124方芳,杨士元,侯新.基于改进多信号分类法的异步电机转子故障特征分量的提取.中国电机工程学报, 2007, 27(30): 72-76
125彭志科,何永勇,卢青.用小波时频分析方法研究发电机碰摩故障特.中国电机工程学报,2003,23(5):75-79.
126 I. S. Cade, P. S. Keogh, M. N. Sahinkaya. Fault Identification in Rotor/Magnetic Bearing Systems Using Discrete Time Wavelet Coefficients. IEEE/ASME Transactions on Mechatronics, 2005, 10(6): 648-657
127 J.M. Lee, S.J. Kim, Y. Hwang, C.S. Song. Diagnosis of Mechanical Fault Signals Using Continuous Hidden Markov Model. Journal of Sound and Vibration, 2004, 276: 1065–1080
128 J.R. Jain , T.K. Kundra. Model Based Online Diagnosis of Unbalance and Transverse Fatigue Crack in Rotor Systems. Mechanics Research Communications, 2004, 31: 557–568
129 R. Markert, R. Platz, M. Seidler. Model Based Fault Identification in Rotor Systems by Least Squares Fitting. International Journal of Rotating Machinery, 2001, 7(5): 311-321
130 N. Bachschmid, P. Pennacchi, A. Vania. Identification of multiple faults in rotor systems. Journal of Sound and Vibration, 2002, 254(2): 327-366
131闻苏平,朱报桢,苗永淼,杨小明.离心式压缩机漏气损失计算.流体机械,1998,26(3):27-30
132高金吉.离心压缩机转子的气动推力与轴位移.化工机械, l983, (1):15-21
133黄钟岳,王晓放.透平式压缩机.化学工业出版社, 2004: 124-130
134王维民,高金吉,江志农.高压离心式压缩机轴向推力研究.风机技术,2006,(6): 1-4
135闻苏平,阎宏,张楚华.离心叶轮外侧间隙内的流动计算.流体机械, 2004,32(6):13-15.
136闻苏平,朱报桢,苗永淼.高压离心压缩机轴向推力计算.西安交通大学学报, 1998, 32(11): 63-67
137 Z. X. Han, G. A. C. Pad. A CFD Method for Axial Thrust Load Prediction of Centrifugal Compressor.International Journal of Turbo and Jet Engines,2003,20:1-16.
138沈庆根,卢奂采,高红俐.大型机组轴向力的在线监测.流体机械,1994,22(3): 33-37
139卢奂采.旋转机械轴向力的在线智能监测系统.自动化仪表,1996,17(2):14-17
140史俊光,童水光,许跃敏,汪希萱.旋转机械轴向力在线动态监测的研究.化工机械,1997, 24(5): 41-44
141钟一谔,何衍宗,王正等.转子动力学.清华大学出版社, 1987: 1-100
142 N. E. Huang, Z. Shen, S. R. Long, M. Wu, H. Shih. The Empirical Mode Decomposition and the Hilbert Spectrum for Non-linear and Non-stationary Time Series Analysis. Proceedings of the Royal Society of London Series A—Mathematical Physical and Engineering Sciences, 1998, 454: 903–995.
143 Z. K. Peng, Peter W. Tse, F. L. Chu. An Improved Hilbert-Huang Transform and its Application in Vibration Signal Analysis. Journal of Sound and Vibration, 2005, 286: 187-205
144 Z. Peng, P. Tse, F. Chu. A Comparison Study of Improved Hilbert-Huang Transform and Wavelet Transform: Application toFault Diagnosis for Rolling Bearing. Mechanical Systems and Signal Processing , 2005, 19: 974–988.
145魏霞.基于HHT的往复机械故障诊断研究.哈尔滨工业大学硕士学位论文, 2005: 1-50
146廖庆斌,李舜酩,覃小攀.车辆振动信号的特征提取方法比较.吉林大学学报(工学版), 2007, 37(4): 910-914
147杨建文,贾民平,许飞云,胡建中.基于经验模式分解的旋转机械振动信号降噪处理.中国工程科学, 2005, 7(8): 66-69
148郭小红,徐小辉,赵树强.基于经验模态分解的外弹道降噪方法及应用.宇航学报, 2008, 29(4): 1272-1275,1307
149 Y. B. Liu, Q. Wu, Z. Y. Ma, K. G. Yan. An Improved Hilbert-Huang Transform and its Application in Faults Signal Analysis. PROCEEDING OF The 2006 IEEE International Conference on Mechatronics and automation, Zhengzhou,2006: 2426-2431
150 Q. Wu, Y. B. Liu, K. G. Yan. A New Approach to Improved Hilbert-Huang Transform. Sixth World Congress on Intelligent Control and Automation, Dalian, 2006: 21-23
151闻邦椿,顾家柳,夏松波,王正.高等转子动力学-理论、技术与应用.机械工业出版社, 1999: 50-200
152 M. Xu, R. D. Marangoni. Vibration Analysis of a Motor-flexible Coupling System Subject to a Misalignment and Unbalance, Part 1: Theoretical Mode and Analysis. Journal of Sound and Vibration, 1994, 176:663–679
153 M. Xu, R. D. Marangoni. Vibration Analysis of a Motor-flexible Coupling System Subject to a Misalignment and Unbalance, Part 2: Experimental Validation. Journal of Sound and Vibration, 1994, 176:681–691
154 Y. S. Lee, C. W. Lee. Modelling and Vibration Analysis of Misaligned Rotor-Ball Bearing Systems. Journal of Sound and Vibration, 1999, 224(1): 17-32
155 K. M. AL-HUSSAIN, I. REDMOND. Dynamic Response of Two Rotors Connected by Rigid Mechanical Coupling with Parallel Misalignment. Journal of Sound and Vibration, 2002, 249(3): 483-498
156 A. W. Lee. Misalignment in Rigidy Coupled Rotors. Journal of Sound and Vibration, 2007, 305: 261-271
157王福军.计算流体动力学分析—CFD软件原理与应用.清华大学出版社, 2004: 1-23
158 R. Dekker, R. E. Wildeman, F. A. Van Der Duyn Schouten. A Review of Multi-Component Maintenance Models with Economic Dependence. Mathematical Methods of Operations Research, 1997, 45: 411-435
159 H. Z. Wang. A Survey of Maintenance Policies of Deteriorating Systems.European Journal of Operational Research, 2002, 139: 469-489.
160 L. M. Maillart, X. Fang. Optimal Maintenance Policies for Serial, Multi-machine Systems with Non-instantaneous Repairs. Naval Research Logistics, 2006, 53: 804-813
161 J. Flynn, C. S. Chung. A heuristic algorithm for determining replacement policies in consecutive k-out-of-n systems. Computers & Operations Research, 2004, 31: 1335–1348
162 D. Y. Chen, K. S. Trivedi. Optimization for Condition-based Maintenance with Semi-Markov Decision Process. Reliability Engineering and System Safety, 2005, 90: 25–29
163 M. Marseguerra, E. Zio, L. Podofillini. Condition-based Maintenance Optimization by Means of Generic Algorithms and Monte Carlo Simulation. Reliability Engineering and System Safety, 2002, 77: 151-166
164 J. M. van Noortwijk, P. H. A. J. M. van Gelder. Optimal Maintenance Decisions for Berm Breakwaters. Structural Safety, 1996, 18(4): 293-309
165 B. Saassouh, L. Dieulle, A. Grall. On Line Maintenance Policy for a Deteriorating System with Random Change of Mode. Reliability Engineering and System Safety, 2007, 92: 1677-1685
166 A. Grall, L. Dieulle, C. Be′renguer, M. Roussignol. A Symptotic Failure Rate of a Continuously Monitored System. Reliability Engineering and System Safety, 2006, 91: 126–130
167 A. H. Christer, W. Wang, J. M. Sharp. A State Space Condition Monitoring Model for Furnace Erosion Prediction and Replacement. European Journal of Operational Research, 1997,101: 1-14
168左洪福,张海军,戎翔.基于比例风险模型的航空发动机视情维修决策.航空动力学报, 2006, 21(4): 716-721
169张秀斌,王广伟,郭波.应用比例故障率模型进行基于状态的视情维修决策.电子产品可靠性与环境试验, 2002, 4: 19-22
170 F. Barbera, H. Schneider, E. Watson. A Condition Based Maintenance Model for a Two-unit Series System. European Journal of Operational Research, 1999, 116: 281–290
171 J. M. van Noortwijk. A Survey of the Application of Gamma Processes in Maintenance. Reliability Engineering and System Safety, In press
172茆诗松.贝叶斯统计.中国统计出版社,1999:1-20
173 L. Doyen, O. Gaudoin. Classes of Imperfect Repair Models Based on Reduction of Failure Intensity on Virtual Age. Reliability Engineering System Safety, 2004, 84: 45-56
174 H. Pham, H. Wang. Imperfect Maintenance. Eur J Oper Res, 1996, 94:438–52
175 M. Brown, F. Proschan Imperfect Repair . J Appl Prob, 1983, 20: 851–9.
176 M. Bartholomew-Biggs, M. J. Zuo, X. H. Li. Modelling and Optimizing Sequential Imperfect Preventive Maintenance. Reliability Engineering and System Safety, in press
177徐克俊,金星,郑永煌编著.航天发射场可靠性安全性评估与分析技术.国防工业出版社, 2006: 50-100
178陈云翔主编.可靠性与维修性工程.国防工业出版社, 2007: 178-202
179徐玖平,李军.多目标决策的理论与方法.清华大学出版社, 2005:89-91
180 K. Das, R. S. Lashkari, S. Sengupta. Machine Reliability and Preventive Maintenance Planning for Cellular Manufacturing Systems. European Journal of Operational Research, 2007,183: 162-180
181 B. Kardon, L. D. Fredendall. Incorporating Overall Probability of System Failure into a Preventive Maintenance Model for a Serial System. Journal of Quality in Maintenance Engineering, 2002,8(4): 331–345.
182姜兴渭,宋政吉,王晓晨.可靠性工程技术.哈尔滨工业大学出版社, 2005: 1-50
183邓爱民,陈循,张春华,汪亚顺.基于性能退化数据的可靠性评估.宇航学报, 2006, 27(3): 546-552.
184 D. Xu, W. B. Zhao. Reliability Prediction using Multivariate Degradation data. Proceedings Annual Reliability and Maintainability Symposium, The City of Alexandria, 2005: 337-341
185 V. Crk. Reliability Assessment from Degradation Data. Proceedings Annual Reliability and Maitainability Symposium, 2000: 155-161
186 J. C. Lu, W. Q. Meeker. Using Degradation Measures to Estimationa Time to Failure Distribution. Technometrics, 1993, 35(2): 161-174
187 R. B. Chinnam. On-line Reliabiliy Estimation for Individual Components using Statistical Degradation Signal Models. Qual. Reliab. Engng. Int. 2002, 18: 53–73
188 D. Kumar, B. Klefsjo. Proportional Hazards Model: a Review. Reliability and System Safety, 1994, 44: 177-188
189 M. Stamatelatos. Fault Tree Handbook with Aerospace Applications. NASA, 2002: 5-35
190 H. Lu, W. J. Kolarik, S. S. Lu. Real-time Performance Reliability Prediction. IEEE Transaction on Reliability, 2001, 50: 353 - 357.
191 V. Chen. Reliability-based Reliability in Outdoor Environments. Dissertation for the Doctoral Degree of Iowa State University, 2001: 23-97
192赵建印.基于性能退化数据的可靠性建模与应用研究.国防科技大学博士学位论文.2005: 37-108
193 P. Wang. System Reliability Prediction Based on Degradation Modeling Considering Field Operating Stress Scenarios. Dissertation for the Doctoral Degree of The State University of New Jersey, 2003: 43-79
194赵炤,董豆豆,周经伦,冯静.基于贝叶斯方法的退化失效型产品实时可靠性评估.国防科技大学学报,2007,29(6):116-120.
195 R. Soland. Use of the Weibull Distribution in Bayesian Decision Theory. Research Analysis Corporation, McLean, VA, 1966: Report no.RAC-TP-225
196 R. Soland. Bayesian Analysis of the Weibull Process with Unknown Scale and Shape Parameters. IEEE Transactions on Reliability, 1969, 18: 181–184
197 A. A. Soliman, A. H. Abd Ellah, K. S. Sultan. Comparison of Estimates Using Record Statistics from Weibull Model: Bayesian and non-Bayesian Approaches. Computational Statistics & Data Analysis, 2006, 51: 2065-2077.
