# Design and implementation of aeroengine fault data simulation generator

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## Abstract

As a core component of an aircraft, once the aeroengine occurs faults, its safety and reliability reduce during the flight. These faults cause unpredictable consequences. Therefore, it is necessary to study how to model the faults of the engine. Based on Simulink software, aeroengine simulation model is established from aeroengine mathematical model which can be derived from aerothermodynamics equations. This paper Simulates various typical faults to aeroengine simulation model, the simulation results show that the designed model can correctly obtain the engine aerothermodynamics export parameters and common faults data, verifying the rationality and effectiveness of the model. The simulation generator provides a visual tool for engine modeling, and supplies data support for aeroengine fault diagnosis and prediction.

## Keywords

Aeroengine Simulink Aerothermodynamics model Component level modeling Fault simulation## 1 Introduction

The aeroengine is a highly complicated and precise nonlinear thermodynamic system, it is the heart of the aircraft. Once the engine fails, it causes a serious threat to the performance and reliability of the aircraft. Therefore, it is of great significance to analyze and research the fault data of aeroengine in order to the safety of the aircraft during flight. Obtaining actual flight data of aircraft engines is difficult and impractical in different situations and various fault conditions. The engine running process can be simulated by this model to get these data, so modeling and simulation of aeroengine are valuable.

Aeroengines have been modeled and simulated by several researchers to obtain their dynamic and steady-state parameter data. Chun-Yang et al. [1] established a mathematical model of the equilibrium manifold of a nonlinear system based on the test data of a turbofan engine. The high-pressure speed is used as the scheduling variable, and the coefficients of the model are obtained by polynomial least squares fitting. At any time, the similar performance parameters for each state can be obtained with the change law of the high-pressure rotor conversion speed, so as to simulate the turbofan engine. When using the equilibrium manifold model, test data is used as the data foundation. Fei et al. [2] used Matlab/Simulink to simulate the general component-level model of a certain type of twin-shaft turbofan engine. The S function and the algebraic ring problem in the model needed to be solved with Newton–Raphson iteration method, which complicates the modeling process. Foreign literatures on aeroengine mainly focus on the research of turboprop engine model [3, 4] and performance simulation [5, 6]. Due to the structural differences of turboprop engines and the confidentiality of design departments, the relevant literatures about the basic and more accurate aerothermal simulation calculation of turboprop engines have not been consulted [7], so the simulation research on fault data is even less. Literature [8], the integrated system is used to model the engine system, and the performance simulation of the engine under various working situations is realized. However, when applied to the 3D/2D interpolation algorithm, a large amount of experimental data is needed, yet it is difficult to obtain a large amount of engine experimental data actually. Literature [9], the CAT-P80 jet aviation gas turbine is used as the research object. The simulation model is established by using Matlab software. The simulation results can accurately reflect the steady-state performance of the gas turbine, but the simulation of the fault data is poverty. Ren Zhibin of Shanghai Jiaotong University [10] modeled and simulated the aero-engine tail nozzle based on Modelica/Dymola software, and realized the performance simulation under non-design speed and small flow conditions. Yao [11] of Nanjing University of Aeronautics and Astronautics used EcosimPro software to carry out component-based aeroengine modeling technology research. Based on a twin-shaft turbofan engine, steady-state simulation and dynamic real-time simulation research were carried out. The simulation results indicates that the engine mathematical model fully meets the real-time requirements and has good stable dynamic simulation accuracy. Sujie et al. [12] of the Institute of Automation, Chinese Academy of Sciences, based on the PROOSIS software to establish aeroengine airway parameter model, obtained the monitoring parameter data under different conditions. Although these softwares are great simple and high precise for modeling different types of aeroengines, this software is not universal and confidential, which is not conducive to scientific research. For aeroengine aerodynamic parameters modeling and simulation, most of the research is only for the simulation data under normal conditions, but few on the fault data simulation.

Due to the generality and openness of Matlab, and the Simulink module library included in the software, the system model can be highly visualized. Therefore, this paper uses the Simulink module library to model the aerothermodynamics equations of various components of the aeroengine and package them as sub-modules, which can realize the visualization of the normal operation process of the engine. The aerothermodynamics equations of the engine components are expressed as Simulink sub-modules, these components include the intake port, fan, compressor, combustion chamber, high pressure turbine, low pressure turbine, mixing chamber and tail nozzle. After sub-modules of these components are built, they are linked together by the common working equation of the aeroengine in the dynamic process, and constrains each other. The simulation parameters, simulation algorithm and other related parameters are set to get the simulation results under the normal operation of the engine. Because it is difficult to obtain the fault data in the process of aeroengine operation, it is crucial to analyze and study the fault data of aeroengine in the actual process. The fault can be found to a certain extent to avoid the occurrence of the fault situation and the unpredictable disaster. Because of the importance of fault data for subsequent fault trend prediction, this paper obtains different fault simulation results by adding different faults according to different fault environments at the input of the aerothermodynamics model, so as to obtain different fault data.

## 2 Aeroengine component level simulation modeling

In order to simulate typical engine faults, a simulation model of its normally operating process must be established. In this section, the modeling process of engine component level based on Simulink is given in detail. The modeling methods commonly used in aeroengines are mechanism modeling and identification modeling [13]. Mechanism modeling is used in this paper, is also called component-level modeling. According to the working principle of aeroengine and aerothermodynamics equation [14], the component-level mathematical model is established. The components of the engine are connected together to obtain the dynamic and static characteristics by the common working equations of the engine power balance and flow balance. After the overall modeling of the engine is completed, the export parameter data of each component is obtained by setting the aerothermodynamics parameters and coefficients of the model.

### 2.1 Aerothermodynamics model and modeling process of each component

Independent component modules are built according to the aerodynamic equations of the aeroengine and its components. Due to the complexity of the aerodynamic thermal process inside the aeroengine, the aerothermodynamics model of each component is packaged as a subsystem module.

#### 2.1.1 Aerothermodynamics mathematical model of the inlet and Simulink simulation module

*T*

_{0}and atmospheric pressure \(P_{0}\) are described as Eqs. 1 and 2 respectively.

#### 2.1.2 Fan’s aerothermodynamics calculation and Simulink simulation module

The outlet pressure \(P_{2.5II}\) and temperature \(T_{2.5II}\) of the outer duct of the fan are equal to the outlet pressure \(P_{2.5}\) and temperature \(T_{2.5}\) of the fan.

#### 2.1.3 Calculation of aerothermodynamics of compressor and Simulink simulation module

When the high pressure compressor extracts cold air, at this time, the high and low pressure turbines are cooled, and the outlet flow rate of the high pressure compressor should be appropriately corrected.

#### 2.1.4 Aerothermodynamics calculation of the combustion chamber and Simulink simulation module

#### 2.1.5 Aerodynamic thermal calculation of high pressure turbine and Simulink simulation module

In the formula, \(r^{\prime} = (k^{\prime} - 1)/k^{\prime}\), \(k^{\prime}\) is the adiabatic index of the gas.

#### 2.1.6 Pneumatic thermal calculation and Simulink simulation module of low pressure turbine

#### 2.1.7 Aerodynamic thermal calculation of the outer culvert of the inlet of the mixing chamber and the Simulink simulation module

#### 2.1.8 Aerodynamic thermal calculation of the mixing chamber outlet and Simulink simulation module

#### 2.1.9 Aerodynamic calculation of the tail nozzle and Simulink simulation module

In the above formula, \(A_{8}\) is the nozzle outlet area, \(C_{0}\) is the flight speed (0 in the interview vehicle), \(a_{cr}\) is the critical sound speed, and when the tail nozzle is in the critical state or supercritical state, the dense flow function can be selected as \(q(\lambda_{8} ) = 1\), \(\lambda_{8} = 1\), \(P_{0}\) is static pressure.

#### 2.1.10 The common working equation of aeroengine and the Simulink simulation module in the dynamic process

After the aerothermodynamics Simulink module of the engine components is built, the components need to work together and be constrained by each other. This restriction exists not only when the engine is stable, but also during the dynamic working of the engine. According to the flow balance and power balance in the dynamic working process of the aeroengine, the common working equation under the common working conditions can be obtained. This paper only considers the influence of engine rotor inertia on the dynamic characteristics of the engine, ignoring the influence of thermal inertia and component channel volume dynamics, and considers that the dynamic process component efficiency and total pressure loss coefficient remain unchanged. The tail nozzle is in a critical state above. Flight conditions are constant. Combustion delays and differences in gas and air flow are ignored.

- (1)The air flow of the fan is equal to the equilibrium equation of the sum of the air flow through the high pressure compressor and the air flow of the outer culvert.$$q_{m,a} - q_{m,aH} - q_{m,aII} = 0.$$(41)
- (2)The high-pressure turbine inlet gas flow rate is equal to the equilibrium equation of the sum of the high-pressure compressor outlet air flow and the fuel flow.$$q_{m,gH} - q_{m,a3} - q_{m,f} = 0.$$(42)
- (3)The equilibrium flow equation between the low pressure turbine inlet gas flow and the high pressure turbine outlet gas flow.$$q_{m,g4.5} - q_{m,gL} = 0.$$(43)
- (4)The gas flow rate of the tail nozzle is equal to the equilibrium equation between the sum of the air flow through the outer culvert and the gas flow at the low pressure turbine outlet.$$q_{m,g8} - q_{m,aII} - q_{m,g5} = 0.$$(44)

- (1)High-pressure shaft power balance equation.where \(P_{TH}\) is the high pressure turbine power \(P_{TH} = q_{m,g4} \pi_{TH}\). \(P_{CH}\) is the high pressure compressor power \(P_{CH} = q_{m,aH} \pi_{CH}\). \(D_{H} (dn_{H} )/dt\) is the dynamic term, the high pressure rotor accelerates the power \(D_{H} = \left( {\pi /30} \right)^{2} J_{H} n_{H}\).$$P_{TH} - P_{CH} - D_{H} \frac{{dn_{H} }}{dt} = 0.$$(45)
- (2)Low-pressure shaft power balance equation.where \(P_{TH}\) is the low pressure turbine power \(P_{TL} = q_{m,g4.5} \pi_{TL}\), \(P_{CL}\) is the fan power \(P_{CL} = q_{m,a} \pi_{CL}\), and \(D_{L} (dn_{L} )/dt\) is the dynamic term, the high voltage rotor accelerates the power \(D_{L} = \left( {\pi /30} \right)^{2} J_{L} n_{L}\).$$P_{TL} - P_{CL} - D_{L} \frac{{dn_{L} }}{dt} = 0.$$(46)

### 2.2 Engine overall Simulink model

## 3 Simulation and analysis of fault impact

In this section, the aerothermodynamics simulation model of Section II is used. By setting the design point parameters involved in the model, the aerothermodynamics output parameter data of each component under normal operating conditions can be obtained. The fault environment is simulated by adding disturbances or changes to the inputs or models of the aerothermodynamics models of the various components to obtain fault parameter data during engine operation.

### 3.1 Simulation environment and parameter setting

Design point paramaters in aerothermodynamics model

Parameters and coefficients (unit) | Values | Parameters and coefficients (unit) | Values |
---|---|---|---|

Height \(H\) (km) | 3 | Gas adiabatic index \(k^{\prime}\) | 0.03964 |

Mach number \(M\) | 0.7 | High pressure turbine efficiency \(\eta_{{_{TH} }}\) | 0.88 |

Inlet total pressure recovery coefficient \(\sigma_{I}\) | 0.97 | High-pressure compressor pumping capacity is used to cool the proportional coefficient of the high-pressure turbine \(K_{H,col}\) | 0.03 |

Speed of the fan \(n_{L}\) (r/min) | 100 | High pressure turbine design point temperature \(T_{4d}\)(k) | 1100 |

Fan boost ratio \(\pi_{CL}\) | 1.23 | High pressure turbine design point pressure \(P_{4d}\) (\(P_{a}\)) | 123,159 |

Air adiabatic index \(k\) | 1.33 | Low pressure turbine expansion ratio \(\pi_{TL}\) | 2.1 |

High pressure compressor speed \(n_{H}\) (r/min) | 160 | Low pressure turbine efficiency \(\eta_{TL}\) | 0.78 |

High pressure compressor boost ratio \(\pi_{CH}\) | 2.716 | Proportion coefficient for cooling low pressure turbine in high pressure compressor suction \(K_{L,col}\) | 0.04 |

Compressor efficiency \(\eta_{CH}\) | 0.85 | Low pressure turbine design point temperature \(T_{4.5d}\) (K) | 1150 |

High pressure compressor suction coefficient \(K_{col}\) | 0.05 | Low pressure turbine design point pressure \(P_{4.5d}\) (\(P_{a}\)) | 110,000 |

Pumping coefficient \(\alpha_{col}\) | 0.045 | Concentrated channel area at the entrance of the mixing chamber \(A_{5I}\) (\(m^{2}\)) | 0.29 |

Air enthusiasm \(h_{f}\)(kJ/kg) | 1.5 | Total pressure recovery coefficient of the outer culvert fan outlet to the inlet of the mixing chamber \(\sigma_{II}\) | 0.93 |

Gas enthusiasm \(h_{a}\) (kJ/kg) | 1.3 | Outside tunnel area at the entrance of the mixing chamber \(A_{5II}\) (\(m^{2}\)) | 0.29 |

Fuel enthusiasm \(h_{g}\) (kJ/kg) | 1.4 | Mixing chamber total pressure recovery coefficient \(\sigma_{cm}\) | 0.98 |

Fuel calorific value \(H_{u}\) (kJ/kg) | 42,900 | Tail nozzle flow loss coefficient \(\sigma_{NZ}\) | 0.93 |

Combustion chamber total pressure recovery coefficient \(\sigma_{b}\) | 0.95 | Tail nozzle outlet pipe area \(A_{8}\) (\(m^{2}\)) | 0.4 |

High pressure turbine expansion ratio \(\pi_{TH}\) | 3 | Critical speed of sound \(a_{cr}\) (m/s) | 316.4 |

### 3.2 Simulation output of engine normal working process

Figure 12 shows the output curve of aerothermodynamics parameters of the compressor, combustion chamber and tail nozzle respectively. The model parameters set in Table 1 are substituted into the aerothermodynamics equations of each component to check the export parameters and models of each component. The output parameters after simulation are basically the same, which verifies the correctness of the model.

### 3.3 Fault simulation and results analysis based on component level model

Aero-engine is a kind of machine with multiple faults, which is expensive to manufacture. It is vulnerable to external environmental impact and abnormal changes and faults during operation. Because it is very difficult and unrealistic to obtain the fault data during flight, according to the different forms of failure, the fault can be simulated by superimposing disturbances or abnormal changes on the input or middle parts of the components of the aeroengine model established in Section II, depending on the manifestation of the different faults. Then adding faults and observing them at the output of each component, and obtain the simulation output result of common faults to realize the engine fault data generation.

Because the abnormal aerodynamic thermal parameters contain a large amount of fault information [19], the engine can operate stably in the normal state on the basis of the engine component level model in view of the occurrence of engine failure. At this time, several typical faults of the engine can be simulated by setting up at the input or the middle part of the model. Abnormal disturbances and changes are set at a certain time point to simulate abnormal changes according to the corresponding performance parameters of a fault decrease or increase, so as to simulate the characteristics of the fault and obtain the changes of aerodynamic thermal parameters of the engine components at the inlet and outlet.

#### 3.3.1 Compressor surge fault simulation

According to the performance of compressor surge fault, the faults are simulated. When surge failure occurs, the abnormal phenomena can be mainly manifested in the change of engine sound from sharp to low, strong mechanical vibration, large fluctuation of compressor flow, engine flame out, or even aerial parking, and the increase of engine exhaust temperature, the increase of exhaust thermometer indication, due to surge into the combustion chamber air. The quantity of gas decreases and the gas temperature at the exit of the combustion chamber rises [20]. Compressor surge is an unstable working state of compressor. It is a phenomenon of low frequency and high amplitude airflow oscillation along the compressor axis caused by the sudden decrease of air flow at the compressor inlet [21]. Therefore, the fault can be simulated by adding a large fluctuation vibration signal to the compressor flow.

Since the surge failure of the compressor is manifested by a large fluctuation in the air flow, the low frequency and high amplitude air flow oscillation occurs along the compressor axis, and the gas temperature at the outlet of the combustion chamber rises. The simulation results are as follows.

#### 3.3.2 Simulation of combustion chamber atomization failure

The performance of atomization failure from the combustion chamber can be characterized by a local increase in combustion chamber temperature. The simulation results are as follows.

#### 3.3.3 Tail nozzle thrust drop failure

The performance of the thrust failure from the tail nozzle can be characterized by a sudden drop in the thrust of the tail nozzle. The simulation results are as follows.

In summary, when the system fails, the aerothermodynamics parameters of the model entrance and exit will change, which will destroy the operational stability of the original system. The simulation results show that the model can simulate the fault environment of the aeroengine well.

## 4 Conclusion

Based on the aerothermodynamics equation of aeroengine, this paper establishes a component-level model of the aeroengine, including sub-modules of the intake port, fan, compressor, combustion chamber, outer duct, high-pressure turbine, low-pressure turbine and tail nozzle package. And through the common working equation to constrain and link each module, realize the overall model of the engine, and then set the corresponding parameters, add different fault types based on the component level model, and realize the problem that the engine normal and fault data are difficult to obtain, which can provide data foundation for fault diagnosis and fault prediction, and also provide a tool for visual modeling and Simulation of complex systems.

## Notes

### Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 91646108). Thanks to the advice of the younger brother and sister.

### Author contributions

A conducted the research. B was corresponding author. CD provided paper revisions. A was the first author, and wrote the paper. All authors had approved the final version.

### Compliance with ethical standards

### Conflict of interest

The authors declare no conflict of interest.

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