SVM-Based Multi-Sensor Information Fusion Technology Research in the Diesel Engine Fault Diagnosis

Jian-xin Lv (), Jia Jia () and Chun-ming Zhang
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Jian-xin Lv: Engineering College of Armed Police Force
Jia Jia: Engineering College of Armed Police Force
Chun-ming Zhang: Engineering College of Armed Police Force

Chapter Chapter 94 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 891-896 from Springer

Abstract: Abstract According to engine’s characteristics of running mechanism and prone to failure, using integration based on the sub-module decision-making output multi-sensor information fusion model, this paper discusses the use of SVM-based multi-sensor information fusion technology on the diesel engine fault diagnosis. As the real data of the fault vehicles experiment shows, compared to the traditional diagnostic methods, SVM-based multi-sensor information fusion technology is more effective on identifying the agricultural diesel failure type.

Keywords: Diesel engine; Fault diagnosis; Multi-sensor information fusion; Support vector machine (SVM) (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38391-5_94

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DOI: 10.1007/978-3-642-38391-5_94

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