Study On Electromechanical Equipment Health Status Evaluation Of Different Stages Of Equipment Life

With the continuous improvement of intellectualization, complication andlarge-scale of electromechanical equipment, the halt production loss ofelectromechanical equipment becomes higher and higher, and the difficulty ofelectromechanical equipment maintenance is also increasing. So, it is of greatimportance to accurately assess the current health status of equipment for equipmentmaintenance. But how to evaluate the health status of electromechanical equipment isnot only the difficult problem for the users of the products but also a research topic forscientific research personnel. This paper mainly researches electromechanicalequipment health status evaluation of equipment health management.At first, the life prediction model is established. By using the improved geneticalgorithm to estimate parameter of weibull lifetime distribution, thus equipment lifedistribution model is established. The improved genetic algorithm can not only quicklyconclude estimation value of the parameters, but also its precision is more accurate thanthe general methods, such as maximum likelihood estimation, etc.Secondly, the health status evaluation model is established. From the functionstructure and the use time of electromechanical equipment, we build double evaluationsystem based on the function structure and life stage system. On the one hand, thestructure of electromechanical equipment is divided. Then evaluate its structure byextracting feature vector of the key parts. On the other hand, the state of its health isobtained according to the different life stages of the key components of theelectromechanical equipment, which is based on the perspective of life cycle. Finallythe health value of the equipment is obtained through fuzzy comprehensive informationin these two aspects.At last, the weighing value is determined. Through combining the improvedgenetic algorithm with analytic hierarchy process, the index weight is obtained. Theproblem of consistency of analytic hierarchy process (AHP) is transformed to theobjective function of genetic algorithm. In this way, on the one hand, the precision canbe improved, on the other hand, genetic algorithm can be used. Through programming,the weight value can be quickly obtained. On this basis, the dynamic evaluation systemis established according to the equipment of the key components in the different lifecycle to adjust the weights, which makes the evaluation becomes more scientific and reasonable. Laboratory platform instance verify the validity of the method.