A real-time mathematical model for two dimensional tidal flow and water quality is presented in this paper. The control-volume-based-finite-difference method and the 'power interpolation distribution' advocate...A real-time mathematical model for two dimensional tidal flow and water quality is presented in this paper. The control-volume-based-finite-difference method and the 'power interpolation distribution' advocated by Patankar [4] have been employed, and new boundary condition for tidal flow is recommended. The model is un- conditionally stable and convergent, and able to deal with irregular estuarine topography and movable boundary problems. Practical application of the model is illustrated by an example for the Swatou Bay. A fair agreement be- tween the values measured and computed demonstrates the validity of the model developed.展开更多
The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process m...The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network(BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.展开更多
文摘A real-time mathematical model for two dimensional tidal flow and water quality is presented in this paper. The control-volume-based-finite-difference method and the 'power interpolation distribution' advocated by Patankar [4] have been employed, and new boundary condition for tidal flow is recommended. The model is un- conditionally stable and convergent, and able to deal with irregular estuarine topography and movable boundary problems. Practical application of the model is illustrated by an example for the Swatou Bay. A fair agreement be- tween the values measured and computed demonstrates the validity of the model developed.
基金the National Natural Science Foundation of China(Nos.51405299 and 51175340)the Natural Science Foundation of Shanghai(No.14ZR1428700)
文摘The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network(BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.
