Remaining useful life prediction for auxiliary power unit based on particle filter

2020 ◽  
Vol 234 (15) ◽  
pp. 2211-2217
Author(s):  
Jiachen Guo ◽  
Jing Cai ◽  
Heng Jiang ◽  
Xin Li
Keyword(s):  
Particle Filter ◽  
Power Unit ◽  
Engineering Application ◽  
Remaining Useful Life ◽  
Civil Aviation ◽  
Recursive Feature Elimination ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
High Prediction ◽  
Useful Life

Auxiliary power unit is one of the indispensable systems for civil aviation aircraft but the traditional planned maintenance cannot meet the actual needs of airlines. In this work, the key performance parameters of the auxiliary power unit are selected by using recursive feature elimination method. With the selected parameters, the remaining useful flight cycle of the auxiliary power unit is predicted by applying particle filter techniques. Some improved algorithms such as Gaussian particle filter and auxiliary particle filter are also compared. The experimental results demonstrate that the particle filter-based method has high prediction accuracy and engineering application value.

scholarly journals In-situ remaining useful life prediction of aircraft auxiliary power unit based on quantitative analysis of on-wing sensing data

2020 ◽  
Vol 12 (3) ◽  
pp. 168781402091147
Author(s):  
Liansheng Liu ◽  
Qing Guo ◽  
Lulu Wang ◽  
Datong Liu
Keyword(s):  
Power Unit ◽  
Life Prediction ◽  
Health Management ◽  
Remaining Useful Life ◽  
Maintenance And Repair ◽  
Sensing Data ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Useful Life

The in-situ prognostics and health management of aircraft auxiliary power unit faces difficulty using the sparse on-wing sensing data. As the key technology of prognostics and health management, remaining useful life prediction of in-situ aircraft auxiliary power unit is hard to achieve accurate results. To solve this problem, we propose one kind of quantitative analysis of its on-wing sensing data to implement remaining useful life prediction of auxiliary power unit. Except the most important performance parameter exhaust gas temperature, the other potential parameters are utilized based on mutual information, which can be used as the quantitative metric. In this way, the quantitative threshold of mutual information for enhancing remaining useful life prediction result can be determined. The implemented cross-validation experiments verify the effectiveness of the proposed method. The real on-wing sensing data of auxiliary power unit for experiment are from China Southern Airlines Company Limited Shenyang Maintenance Base, which spends over $6.5 million on auxiliary power unit maintenance and repair each year for the fleet of over 500 aircrafts. Although the relative improvement is not too large, it is helpful to reduce the maintenance and repair cost.

Aircraft auxiliary power unit performance assessment and remaining useful life evaluation for predictive maintenance

2019 ◽  
Vol 234 (6) ◽  
pp. 804-816
Author(s):  
Fangyuan Wang ◽  
Jianzhong Sun ◽  
Xinchao Liu ◽  
Cui Liu
Keyword(s):  
Power Unit ◽  
Performance Degradation ◽  
Remaining Useful Life ◽  
Commercial Aircraft ◽  
Baseline Model ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Auxiliary Power Units ◽  
Useful Life ◽  
Condition Monitoring System

Modern commercial aircraft are usually configured with aircraft condition monitoring system to collect the operating data of subsystems and components, which can be used for airborne system health monitoring and predictive maintenance. This paper presents a baseline model based aircraft auxiliary power unit performance assessment and remaining useful life prediction method using aircraft condition monitoring system reports data, which can facilitate a cost-effective management of auxiliary power units of aircraft fleet. Firstly, the performance baseline model for auxiliary power unit is established using random forest method. Then a health index characterizing the performance degradation of in-service auxiliary power units is obtained based on the performance baseline model. Finally, the performance degradation trend is predicted using Bayesian dynamic linear model. To improve the prediction accuracy, four performance baseline models are established from the data of auxiliary power units under different operating conditions, among which an optimal model is determined. This data-driven baseline model can be used to quantify the performance degradation of auxiliary power units in service, and can be further used to evaluate the remaining useful life of auxiliary power unit using a Bayesian dynamic model. The developed approach is applied on a real data set from 22 auxiliary power units of a commercial aircraft fleet. The results show that the computed health index can effectively characterize the auxiliary power units performance degradation and the remaining useful life relative prediction errors are less than 4% when auxiliary power unit enters the rapid degradation stage. This would allow operators to accurately assess the performance degradation for the auxiliary power units and further proactively plan future maintenance events based on remaining useful life prediction.

A Hybrid Method of Remaining Useful Life Prediction for Aircraft Auxiliary Power Unit

2020 ◽  
Vol 20 (14) ◽  
pp. 7848-7858 ◽  
Author(s):  
Xiaolei Liu ◽  
Liansheng Liu ◽  
Datong Liu ◽  
Lulu Wang ◽  
Qing Guo ◽  
...  
Keyword(s):  
Power Unit ◽  
Hybrid Method ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Useful Life

Particle Filter Approach for IGBT Remaining Useful Life

2014 ◽  
Vol 981 ◽  
pp. 86-89 ◽  
Author(s):  
Min Li ◽  
Jiong Jiong Zhu ◽  
Bin Long
Keyword(s):  
Particle Filter ◽  
Prediction Method ◽  
Remaining Useful Life ◽  
Temperature Cycling ◽  
Widespread Application ◽  
High Prediction ◽  
Useful Life ◽  
Temperature Cycling Test ◽  
Filter Approach ◽  
Deterioration Parameters

With the increasingly widespread application, the requirement for PHM of IGBT is becoming gradually urgent. Based on particle filter theory, a method for remaining useful life (RUL) prediction of IGBT is proposed. Firstly, the deterioration parameters on-state VCE and ICE are extracted by temperature cycling test, then a model is developed based on the degradation trend exhibited by deterioration parameters. In the end, PF approach is applied to the IGBT's RUL prediction with the mentioned model. The results show that the proposed prediction method can achieve high prediction accuracy.

Approximation of Payback Period of Fuel Cell Auxiliary Power Unit for Large Trucks

2009 ◽  
Vol 129 (2) ◽  
pp. 228-229
Author(s):  
Noboru Katayama ◽  
Hideyuki Kamiyama ◽  
Yusuke Kudo ◽  
Sumio Kogoshi ◽  
Takafumi Fukada
Keyword(s):  
Fuel Cell ◽  
Power Unit ◽  
Payback Period ◽  
Auxiliary Power Unit ◽  
Auxiliary Power

Electric auxiliary power unit for Shuttle evolution

1989 ◽  
Author(s):  
DOUG MEYER ◽  
KENT WEBER ◽  
WALTER SCOTT
Keyword(s):  
Power Unit ◽  
Auxiliary Power Unit ◽  
Auxiliary Power
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