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contributor authorMahdi Alavinia, Sayyid
contributor authorAli Sadrnia, Mohammad
contributor authorJavad Khosrowjerdi, Mohammad
contributor authorMehdi Fateh, Mohammad
date accessioned2017-05-09T01:08:01Z
date available2017-05-09T01:08:01Z
date issued2014
identifier issn1528-8919
identifier othergtp_136_10_102602.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/154829
description abstractThis 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.
publisherThe American Society of Mechanical Engineers (ASME)
titleStable and Efficient Operation of Gas Compressor With Improving of Surge Detection System
typeJournal Paper
journal volume136
journal issue10
journal titleJournal of Engineering for Gas Turbines and Power
identifier doi10.1115/1.4027371
journal fristpage102602
journal lastpage102602
identifier eissn0742-4795
treeJournal of Engineering for Gas Turbines and Power:;2014:;volume( 136 ):;issue: 010
contenttypeFulltext


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