飞机座舱供气品质分析

针对飞机供气异味问题,从飞机座舱供气原理出发,分析可能影响飞机座舱供气品质的因素,通过排查和检测找到供气异味的来源,采取相应措施保证座舱的供气品质,提出座舱供气品质的控制途径,为进一步的飞机座舱空气品质研究提供参考。     

Design for aircraft engine multi-objective controllers with switching characteristics

The aircraft engine multi-loop control system is described and the switching control theory is introduced to solve the regulating and protecting control problems in this paper. The aircraft engine multi-loop control system is firstly described and the control problems are formulated. Secondly, the theory of the smooth switching control is devoted and a new extended scheme for the smooth switching of a switched control system is introduced. Then, for the key technologies of aero-engines switching control, a design algorithm is presented which can determine which candidate controller should be put in feedback with the plant to achieve a desired performance and the procedure to design the aircraft engine multi-loop control system is detailed. The switching performance objectives and the switching scheme are given and a family of PID controllers and compensators is designed. The simulation shows that using the switching control design method can not only improve the dynamic performance of the aircraft engine control system and reduce the switching times, but also guarantee the stability in some peculiar occasions.     

Efficiency optimized fuel supply strategy of aircraft engine based on air-fuel ratio control

Accurate fuel injection control of aircraft engine can optimize the energy efficiency of UAV power system while meeting the propeller speed requirement. Traditional injection control method such as open-loop calibration causes instability of fuel supply which brings the risk of power loss of UAV. Considering that the closed-loop control of AFR can ensure a stable fuel feeding, this paper proposes an AFR control based fuel supply strategy in order to improve the efficiency of fuel-powered UAV while obtaining the required engine speed. According to the optimum fuel injection results, we implement fuzzy-PID method to control the set AFR in different situations. Through simulation and experiment studies, the results indicate that, to begin with, the calibrated mathematical model of the aircraft engine is effective. Next, this fuel supply strategy based on AFR control can normally realize the engine speed regulation, and the applied control algorithm can eliminate the overshoot of AFR throughout all the working progress. What is more,the fuel supply strategy can averagely shorten the response time of the engine speed by about two seconds. In addition, compared with the open-loop calibration, in this work the power efficiency is improved by 9% to 33%. Last but not the least, the endurance can be improved by 30 min with a normal engine speed. This paper can be a reference for the optimization of UAV aircraft engine.     

NOx emissions of turbofan powered unmanned aerial vehicle for complete flight cycle

Unmanned Aerial Vehicles (UAVs) have been getting more and more popular in both civil and military arena. Similar to manned aircraft, their propulsion systems or engines emit harmful gases such as nitrogen oxides. Since UAVs have different mission profiles and operational parameters than manned aircraft, it is worthy to investigate their NO_x emissions. Therefore, in this study, NO_x emissions of a turbofan powered UAV for complete flight cycle was calculated and optimized within a range of altitude and speed parameters. NO_x emissions were calculated based on ICAO ground test data and corrected to any speed and altitude during flight legs using both Boeing Fuel Flow Method 2 and DLR Fuel Flow Method. Total NO_x emissions were calculated for complete flight cycles for different altitude and speed parameters. Numerical results were presented graphically and additionally optimization studies were conducted. Optimization studies include determination and comparison of speed and altitude for minimum NO_x emissions by the two fuel flow methods and maximum loiter time achievable by UAV.     

Optimization on conventional and electric air-cycle refrigeration systems of aircraft: A short-cut method and analysis

The air-cycle refrigeration system is widely used in commercial and military aircraft, and its efficiency greatly affects aircraft performance. Nowadays, this system requires a more efficient design and optimization method. In this paper, a short-cut optimization method with high efficiency and effectiveness is introduced for both conventional and electric air-cycle refrigeration systems. Based on the system characteristics, a four-layer parameter matching algorithm is designed which avoids computational difficulty caused by simultaneous equations. Fuel penalty is chosen as the objective function of optimization; design variables are reduced based on sensitivity analysis to improve optimization efficiency. The results show that the 3-variable optimization of the conventional air-cycle refrigeration system can obtain almost the same results as the traditional 6-variable optimization in that these two optimizations can both significantly reduce the fuel penalty. However, the computer running time of the 3-variable optimization is much shorter than that of the 6-variable optimization. The optimal fuel penalty of the electric air-cycle refrigeration system is lower than that of the conventional one. This study can provide reference for optimizing the air-cycle refrigeration system of aircraft.     

Aircraft engine fault detection based on grouped convolutional denoising autoencoders

Many existing aircraft engine fault detection methods are highly dependent on performance deviation data that are provided by the original equipment manufacturer. To improve the independent engine fault detection ability, Aircraft Communications Addressing and Reporting System (ACARS) data can be used. However, owing to the characteristics of high dimension, complex correlations between parameters, and large noise content, it is difficult for existing methods to detect faults effectively by using ACARS data. To solve this problem, a novel engine fault detection method based on original ACARS data is proposed. First, inspired by computer vision methods, all variables were divided into separated groups according to their correlations. Then, an improved convolutional denoising autoencoder was used to extract the features of each group. Finally, all of the extracted features were fused to form feature vectors. Thereby, fault samples could be identified based on these feature vectors. Experiments were conducted to validate the effectiveness and efficiency of our method and other competing methods by considering real ACARS data as the data source. The results reveal the good performance of our method with regard to comprehensive fault detection and robustness. Additionally, the computational and time costs of our method are shown to be relatively low.     

Aircraft air conditioning system health state estimation and prediction for predictive maintenance

The vast potential of system health monitoring and condition based maintenance on modern commercial aircraft is being realized through the innovative use of Airplane Condition Monitoring System (ACMS) data. However there are few methods addressing the issues of failure prognostics and predictive maintenance for commercial aircraft Air Conditioning System (ACS). This study developed a Bayesian failure prognostics approach using ACMS data for predictive maintenance of ACS. First, a health index characterizing the ACS health state is inferred from a multiple sensor signals using a data driven method. Then a dynamic linear model is proposed to describe the degradation process for failure prognostics. Bayesian inference formulas are carried out for degradation estimation and prediction. The developed approach is applied on a passenger aircraft fleet with ACMS data recorded for one year. The analysis of the case study shows that the developed method can produce satisfactory prognostics results, where all the ACS failure precursors are identified in advance, and the relative errors for the failure time prediction made when just entering the degradation warning stage are less than 8%. This would allow operators to proactively plan future maintenance.     

Structural mass prediction in conceptual design of blended-wing-body aircraft

The Blended-Wing-Body (BWB) is an unconventional configuration of aircraft and considered as a potential configuration for future commercial aircraft. One of the difficulties in conceptual design of a BWB aircraft is structural mass prediction due to its unique structural feature. This paper presents a structural mass prediction method for conceptual design of BWB aircraft using a structure analysis and optimization method combined with empirical calibrations. The total BWB structural mass is divided into the ideal load-carrying structural mass, non-ideal mass, and secondary structural mass. Structural finite element analysis and optimization are used to predict the ideal primary structural mass, while the non-ideal mass and secondary structural mass are estimated by empirical methods. A BWB commercial aircraft is used to demonstrate the procedure of the BWB structural mass prediction method. The predicted mass of structural components of the BWB aircraft is presented, and the ratios of the structural component mass to the Maximum TakeOff Mass (MTOM) are discussed. It is found that the ratio of the fuselage mass to the MTOM for the BWB aircraft is much higher than that for a conventional commercial aircraft, and the ratio of the wing mass to the MTOM for the BWB aircraft is slightly lower than that for a conventional aircraft.     

General optimal design of solar-powered unmanned aerial vehicle for priority considering propulsion system

This paper describes the general optimization design method of Solar-Powered Unmanned Aerial Vehicle which priority considering propulsion system planning. Based on the traditional solar powered aircraft design method, the propulsion system top-level target parameters which affect the path planning are integrated into the general optimization design. According to the typical mission requirements of Solar-Powered Unmanned Aerial Vehicle, considering the design variables such as wing area, aspect ratio, design mission date and so on, the general optimization is carried out with the minimum aircraft weight as the optimization objective. The influence of wing area and aspect ratio on the optimal design results is analyzed and compared with the traditional design method. The results show that the general design method of Solar-Powered Unmanned Aerial Vehicle for priority considering propulsion system can greatly reduce the electricity demand of energy storage battery, greatly reduce the aircraft weight of Solar-Powered Unmanned Aerial Vehicle.     

A data-driven health indicator extraction method for aircraft air conditioning system health monitoring

Prognostics and Health Management (PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model, one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System (ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System (ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance.