The active jet noise control received significant attention due to the little influence it has on the engine performance. The active jet noise control is a multivariable problem because it needs to achieve the simultaneous closed-loop control of jet noise and engine performance. Model predictive control (MPC) has great application potentials in the field of multivariable control of aero-engines, but the real-time performance of MPC is intractable. This paper proposed an active jet noise controller of a turbofan engine, based on explicit model predictive control (EMPC). An integrated model of turbofan engine and jet noise, which calculates the engine parameters and jet noise in real time, was established. The online computational burden of MPC was transferred to offline computation using multi-parametric quadratic programming (MPQP). To improve the efficiency of the online positioning algorithm, the sequence search method was replaced by a binary search tree. Step simulations were performed to test the effectiveness of the proposed controller. The results show that the proposed EMPC controller not only achieves the simultaneous control of jet noise and the turbofan engine, but also improve the real-time performance greatly.

Exact component characteristics are required for establishing an accurate component level aeroengine model. When component characteristics is lacking, the dynamic coefficient method based on test data, is suitable for establishing a single-input and single-output aeroengine model. When it is applied to build multiple-input, multiple-output aeroengine models, some parameters are assumed to be unchanged, which causes large error. An improved modeling method based on rig data is proposed to establish a double-input, double-output model for a micro variable-pitch turboprop engine. The input variables are fuel flow and pitch angle, and the output variables are rotational speeds of the core engine and the propeller. First, in order to gather modeling data, a test bench is designed and rig tests are carried out. Then, two conclusions are obtained by analyzing the rig data, based on which, the power turbine output is taken as the function of the core speed and the propeller speed. The established model has the property that the input variables can vary arbitrarily within the defined domain, without any restriction to the output variables. Simulation results showed that the model has a high dynamic and steady-state accuracy. The maximum error was less than 8%. The real-time performance was greatly improved, compared to the component level model.

In a wind power plant of a wind power plant limited liability company, the fixed shaft of the torsion arm of the gear box broke during the operation of a wind power generator set. In order to find out the cause of fracture, the fracture fixed shaft of torsion arm was comprehensively detected and analyzed by means of appearance morphology analysis, chemical composition analysis, mechanical properties testing, microstructure testing and fracture micro-area analysis. The results show that the main reasons for the fracture of the fixed shaft of the torsion arm of the fan gear box are as follows: improper heat treatment process of the fixed shaft of the torsion arm of the gear box causes a large amount of massive ferrite in the material structure, resulting in insufficient strength of the material; the inclusion in the material is serious, resulting in unqualified impact toughness; Shaft surface surfacing Cr - Mn stainless steel material causes the fusion zone C migration form brittle layer, at the same time the vast difference between the state of welding layer and substrate organization fusion zone caused by larger remnants stress, the embrittlement in bond layer to form the intergranular crack crack source, and in the process of the equipment operation under the action of cyclic torsional and impact load, Cracks propagate in a fatiguing manner and lead to eventual fracture.