摘要
To solve the precision and reliability problem of various machinery equipments and military vehicles, some military organisations, the industrial sector and the academia at home and abroad begin to pay attention to the statistical distribution of machining dimensions, material properties and service loads, and the system reliability optimization design with constraints and reliability optimization design of various mechanical parts is studied in this way. However, the above researches focus on solving the strength and the life problem, and no studies have been done on the discrete degree and discrete pattern of other performance indicators. The concept of using a random vector to describe the mechanical parts performance indicators is presented; characteristics between the value of the vector variance matrix determinant and the sum of the diagonal covariance matrix in describing the performance indicators of vector dispersion are studied and compared. A clutch diaphragm spring is set as an example, the geometric dimension indicator is described with random vector, and the applicability of using variance matrix determinant and variance matrix trace of geometric dimension vector to describe discrete degree of random vector is studied by using Monte-Carlo simulation method and component discrete degree perturbation method. Also, the effects of different components of diaphragm spring geometric dimension vector on the value of covariance matrix determinant and the sum of covariance matrix diagonal of diaphragm spring performance indicators vector are analyzed. The present study shows that the impacts of the dispersion of diaphragm spring cone angle on every performance dispersion are all ranked first, and far exceed that of other dimension dispersion. So it must be strictly controlled in the production process. The result of the research work provides a reference for the design of diaphragm spring, and also it presents a proper method for researching the performance of other mechanical parts.
To solve the precision and reliability problem of various machinery equipments and military vehicles, some military organisations, the industrial sector and the academia at home and abroad begin to pay attention to the statistical distribution of machining dimensions, material properties and service loads, and the system reliability optimization design with constraints and reliability optimization design of various mechanical parts is studied in this way. However, the above researches focus on solving the strength and the life problem, and no studies have been done on the discrete degree and discrete pattern of other performance indicators. The concept of using a random vector to describe the mechanical parts performance indicators is presented; characteristics between the value of the vector variance matrix determinant and the sum of the diagonal covariance matrix in describing the performance indicators of vector dispersion are studied and compared. A clutch diaphragm spring is set as an example, the geometric dimension indicator is described with random vector, and the applicability of using variance matrix determinant and variance matrix trace of geometric dimension vector to describe discrete degree of random vector is studied by using Monte-Carlo simulation method and component discrete degree perturbation method. Also, the effects of different components of diaphragm spring geometric dimension vector on the value of covariance matrix determinant and the sum of covariance matrix diagonal of diaphragm spring performance indicators vector are analyzed. The present study shows that the impacts of the dispersion of diaphragm spring cone angle on every performance dispersion are all ranked first, and far exceed that of other dimension dispersion. So it must be strictly controlled in the production process. The result of the research work provides a reference for the design of diaphragm spring, and also it presents a proper method for researching the performance of other mechanical parts.
