| HUA Peng,ZHU Hai-qing,ZHANG Mao-li,SHI Xiao-min,DENG Jun-xiu.Roughness Prediction and Experimental Study on Grinding Repair of Safety Valve Closure Members[J],47(1):242-248 |
| Roughness Prediction and Experimental Study on Grinding Repair of Safety Valve Closure Members |
| Received:July 20, 2017 Revised:January 20, 2018 |
| View Full Text View/Add Comment Download reader |
| DOI：10.16490/j.cnki.issn.1001-3660.2018.01.038 |
| KeyWord:safety valve closure members grinding BP neural network surface roughness prediction |
| Author | Institution |
| HUA Peng |
School of Mechanical Engineering, Jiangnan University, Wuxi , China |
| ZHU Hai-qing |
School of Mechanical Engineering, Jiangnan University, Wuxi , China |
| ZHANG Mao-li |
School of Mechanical Engineering, Jiangnan University, Wuxi , China |
| SHI Xiao-min |
School of Mechanical Engineering, Jiangnan University, Wuxi , China |
| DENG Jun-xiu |
School of Mechanical Engineering, Jiangnan University, Wuxi , China |
|
| Hits: |
| Download times: |
| Abstract: |
| The work aims to optimize process parameters of safety valve closure member and improve grinding quality of safety valve sealing surface. With Al2O3 sandpaper as abrasive, law of influence of abrasive grain fineness, grinding time, grinding speed and grinding pressure on surface roughness of valve seat and valve flap was studied by performing orthogonal test. The surface roughness of valve seat and valve flap was measured with roughness tester, and better grinding process parameters were obtained preliminarily. Nonlinear mapping approximation was solved with BP neural network in MATLAB. A surface roughness prediction model was established, and 16 sets of real sample data from grinding process experiment of safety valve were analyzed, and roughness under different process parameters was predicted. The optimal process parameters: abrasive grain fineness of 1500 mesh, grinding pressure of 100 N, grinding speed of 100 r/min, grinding time of 10 min, were obtained preliminarily by performing orthogonal test. In order to further design more comprehensive orthogonal test and validate prediction results of the roughness model, the best grinding scheme obtained was: sandpaper fineness of 1500 mesh, grinding pressure of 120 N, grinding speed of 80 r/min, and grinding time of 12 min. The roughness prediction model can be used to predict surface roughness favorably and obtain the optimal process parameters which may reduce surface roughness to 0.074 μm and effective improve grinding quality. |
| Close |
|
|
|