Prediction of Remaining Useful Life of anAircraft Engine under Unknown Initial Wear

نویسندگان

  • Amit Kumar Jain
  • Pradeep Kundu
  • Bhupesh Kumar Lad
چکیده

Effectiveness of Condition Based Maintenance (CBM) strategy depends on accuracy in prediction of Remaining Useful Life (RUL).Data driven prognosisapproaches are generally used to estimate the RUL of the system. Presence of noise in the system monitored data may affect the accuracy of prediction. One of the sources of data noise is the presence of unknown initial wear in the samples. Present paper illustrates the effect of such initial wear on prediction accuracy and presents the guidelines to handle such initial wears. Two Artificial Neural Network (ANN)models are developed. First model is developed with the help of completedata; while the second model is developed after removing samples with abnormal initial wear.̅and R control chart is used to screen the samples with abnormal initial wear. It is found that the presence of initial wear significantly affects the prediction accuracy. Also, it is found that RUL estimation for a unit with short history tends to produce great uncertainty.Hence, it is recommended that RUL prediction should be continuously updated with age of the unit to increase the effectiveness of CBM policy.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Data Driven Models for Prognostics of High Speed Milling Cutters

Effectiveness of tool condition monitoring strategy depends on accuracy in failure prediction (prognostics) of cutting tools. Data driven approaches are generally used for prognostics of cutting tools. Various prognostics models have been proposed in the literature. Performance of these models in terms of accuracy and applicability are found to be the major constraints for use in real industria...

متن کامل

Enhanced Particle Filtering for Parameter Estimation

Parameter estimation for trending analysis is a generic problem with broad applications. In manufacturing, trending analysis can be applied to tool wear estimation, which not only affects the tool life but also and the quality of a machined product. Consequently, in-situ tool wear monitoring and remaining tool life prediction play a significant role in ensuring precision and cost-effective manu...

متن کامل

Remaining Useful Life Estimation In the Presence of Given Shocks

In a system, prediction of remaining useful lifetime (RUL) of servicing before reaching to a specified breakdown threshold is a very important practical issue, and research in this field is still regarded as an appreciated research gap. Operational environment of an equipment is not constant and changes regarding to stresses and shocks. These random environmental factors accelerate system deter...

متن کامل

Application of multi regressive linear model and neural network for wear prediction

The liner of an ore grinding mill is a critical component in the grinding process, necessary for both high metal recovery and shell protection. From an economic point of view, it is important to keep mill liners in operation as long as possible, minimising the downtime for maintenance or repair. Therefore, predicting their wear is crucial. This paper tests different methods of predicting wear i...

متن کامل

A Numerical Investigation of TBM Disc Cutter Life Prediction in Hard Rocks

There is a direct relationship between the efficiency of mechanized excavation in hard rocks and that of disc cutters. Disc cutter wear is an important effective factor involved in the functionality of tunnel boring machines. Replacement of disc cutters is a time-consuming and costly activity that can significantly reduce the TBM utilization and advance rate, and has a major effect on the total...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014