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Research on fault diagnosis of thermodynamic system based on the network model of internet of things
Author(s) -
Fangcheng He,
Pengcheng Wei
Publication year - 2019
Publication title -
thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci181204158h
Subject(s) - fault (geology) , computer science , matrix (chemical analysis) , fault model , function (biology) , thermodynamic system , turbine , algorithm , data mining , engineering , physics , thermodynamics , materials science , geology , electronic circuit , seismology , composite material , evolutionary biology , electrical engineering , biology
Aiming at the problem that the traditional diagnosis model is difficult to be established accurately, a fault diagnosis algorithm based on the fault diagnosis criterion is constructed to study the fault diagnosis of thermodynamic system based on the network model of internet of things. By analyzing the fault parameters of the equipment system, the algorithm establishes the fault matrix, calculates the mapping relation function corresponding to the states with unknown and known matrix, and obtains the optimal solution of the objective function. It solves the problem that the traditional diagnosis scheme is difficult to accurately diagnose the unknown model. By analyzing the cause and mechanism of the system fault, the diagnosis criterion of each kind of fault is determined. The fault matrix is established by calculation and judgment. The simulation experiment of gas path fault shows that the criterion of turbine blade mechanical damage fault is that the turbine efficiency is reduced by 5%, which is consistent with the theoretical analysis. This shows that the proposed algorithm is effective and the simulated data can be used as technical support for fault diagnosis of similar thermodynamic systems.

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