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Predictive Maintenance of NOx Sensor using Deep Learning: Time series prediction with encoder-decoder LSTM
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In automotive industry there is a growing need for predicting the failure of a component, to achieve the cost saving and customer satisfaction. As failure in a component leads to the work breakdown for the customer. This paper describes an effort in making a prediction failure monitoring model for NOx sensor in trucks. It is a component that used to measure the level of nitrogen oxide emission from the truck. The NOx sensor has chosen because its failure leads to the slowdown of engine efficiency and it is fragile and costly to replace. The data from a good and contaminated NOx sensor which is collated from the test rigs is used the input to the model. This work in this paper shows approach of complementing the Deep Learning models with Machine Learning algorithm to achieve the results. In this work LSTMs are used to detect the gain in NOx sensor and Encoder-Decoder LSTM is used to predict the variables. On top of it Multiple Linear Regression model is used to achieve the end results. The performance of the monitoring model is promising. The approach described in this paper is a general model and not specific to this component, but also can be used for other sensors too as it has a universal kind of approach. 

Place, publisher, year, edition, pages
2019. , p. 44
Keywords [en]
Deep Learning, Predictive Maintenance, LSTM, NOx sensor, Time series prediction, Regression.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-18668OAI: oai:DiVA.org:bth-18668DiVA, id: diva2:1352507
External cooperation
Volvo Group Truck Technologies
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
ETASX Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Supervisors
Examiners
Available from: 2019-09-24 Created: 2019-09-19 Last updated: 2019-09-24Bibliographically approved

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Predictive Maintenance of NOx Sensor using Deep Learning(945 kB)25 downloads
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CiteExportLink to record
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  • apa
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