An Event Correlation Based Approach to Predictive Maintenance

  • Meiling ZhuEmail author
  • Chen Liu
  • Yanbo Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10988)


Predictive maintenance aims at enabling proactive scheduling of maintenance, and thus prevent unexpected equipment failures. Most approaches focus on predicting failures occurring within individual sensors. However, a failure is not always isolated. It probably formed by propagation of trivial anomalies, which are widely regarded as events, among sensors and devices. In this paper, we propose an event correlation discovery algorithm to capture correlations among anomalies/failures. Such correlations can show us lots of clues to the propagation paths. We also extend our previous service hyperlink model to encapsulate such correlations and propose a service-based predictive maintenance approach. Moreover, we have made extensive experiments to verify the effectiveness of our approach.


Event correlation Sensor data Predictive maintenance Proactive data service Service hyperlink 



Funding: This work was supported by National Natural Science Foundation of China (No. 61672042).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyTianjin UniversityTianjinChina
  2. 2.Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream DataNorth China University of TechnologyBeijingChina
  3. 3.Cloud Computing Research CenterNorth China University of TechnologyBeijingChina

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