| contributor author | Mahdi Alavinia, Sayyid | |
| contributor author | Ali Sadrnia, Mohammad | |
| contributor author | Javad Khosrowjerdi, Mohammad | |
| contributor author | Mehdi Fateh, Mohammad | |
| date accessioned | 2017-05-09T01:08:01Z | |
| date available | 2017-05-09T01:08:01Z | |
| date issued | 2014 | |
| identifier issn | 1528-8919 | |
| identifier other | gtp_136_10_102602.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/154829 | |
| description abstract | This paper investigates the application of fault diagnosis (FD) approach for improving performance of compressors within exact operating point determination. Detecting of sensor fault or failure status is more important in the compressor for safetycritical application. No work has previously been reported on the use of the FD system within a compressor surgesuppressing system. Therefore, the main contribution of this paper is presenting different and complementary techniques for surgesuppressing studies via sensor FD. By data acquisition from a nonlinear Moore–Greitzer model, a neural network (NN) and innovation complex decision logic provide residual generation and evaluation blocks in an analytical redundancy FD system, respectively. The proposed FD deals with the mostcommon sensor faults and failures in seven different scenarios according to their nature, such as bias, cutoff, loss of efficiency, and freeze. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Stable and Efficient Operation of Gas Compressor With Improving of Surge Detection System | |
| type | Journal Paper | |
| journal volume | 136 | |
| journal issue | 10 | |
| journal title | Journal of Engineering for Gas Turbines and Power | |
| identifier doi | 10.1115/1.4027371 | |
| journal fristpage | 102602 | |
| journal lastpage | 102602 | |
| identifier eissn | 0742-4795 | |
| tree | Journal of Engineering for Gas Turbines and Power:;2014:;volume( 136 ):;issue: 010 | |
| contenttype | Fulltext | |