Research On System Structure And Decision Model For Condition-Based Maintenance Of Equipment

Modern production equipment is high technology, complex in structure and has strong system performance, and its failure not only displays the strong randomness, but also the loss is very serious. The traditional maintenance ideas and the methods have received the stern challenge, and the condition-based maintenance (CBM) that is more scientific, advanced and effective maintenance idea and way receives the academic circles and enterprise's close attention day by day, and becomes the current hot research topic in maintenance field.Establishing the structural frame of CBM system is helpful to construct the research and development of CBM and to perfect and extend research content of CBM. The decision-making as an important component of CBM system is noticeable important content in CBM work. The structure design of CBM system and thorough research of CBM decision-making process have very important significance and the practical value.The article defines the connotation of CBM, analyzes the characteristics of CBM based on the combing and analysis of research literature of CBM, and has constructed the basic structure frame of CBM system according to a series of functions that CBM system should implement and the need in reality. According to the basic structural frame of CBM system, work content of CBM is given, and three stages of CBM work process and key taches of decision-making process are proposed. According to the present situation of equipment maintenance management of enterprises in our country, The foundations of technology support and management guarantee in implementing CBM are proposed, and the basic principle of implementing CBM is pointed out, and the work process of implementing CBM is elaborated in detail.The article studies and analyzes the decision-making process of CBM systematically and thoroughly.First, the early identification of the defect state is carried on. Based on analysis of the equipment operating characteristics and in view of the deficiencies of the traditional methods, Modeling method of identifying the initiation time of defect is elaborated from two situations, and the situation in which the measured signal is single value is emphasized. Aiming to the situation in which the measured signal is a multi-dimensional vector, using principal component analysis method to draw the characteristic quantity that is data input of modeling is proposed, and the relationship between the multi-dimensional principal components and the state of monitored equipment is established. At the same time, EM algorithm is applied to estimate unknown parameters in the model. In order to enhance the convergence rate of EM algorithm and the accuracy of estimate, the corresponding improvement to the EM algorithm is made. In addition, the computer simulation research for the method and process of identifying the staring time of defect is conducted, and the validity and the accuracy of the method are testified.Next, deterioration degree prediction of defect state is carried on. Based on analysis of the foreseeability of defect state and of the deficiency of the current state prediction modeling methods, the residual life prediction modeling method based on the stochastic filtering theory is elaborated, and bigger improvement is done. One–stage prediction model is extended to two-stage prediction model by supposing the condition monitoring signal in the normal and defective operating stages of the monitored equipment be subject to the distribution of two parameters where the scale parameters have some relationship and the shape parameters are different. At the same time, in order to improve estimate validity and reduce estimate error, the method and the process of model parameter estimate using the maximum likelihood method in the situation of less failure data are proposed. In addition, the computer simulation research for the method and process of the residual life prediction is conducted, and the validity and the accuracy of the method are testified.Finally, based on the identification of defect starting time and prediction of defect state deterioration degree, the decision optimization is made. The maintenance action decision optimization model is established and the solution method is given. Meanwhile two-stage condition monitoring interval optimization simulation model is built using simulation method, and the main simulation step and process are given. Case study testifies and analyzes the feasibility and validity of models related to CBM decision-making process. The result shows that the decision-making process and models can direct the practice of CBM decision very well and make the decision more dynamic and scientific.