105 Extraction Method of Fault Component on Acoustic Signals Generated by an Outboard Marine Engine Based on Characteristic of Paralleled Auto Regressive Model with Extra Input.

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  • SASADA Keiji
    Graduate School of Fisheries Science, National Fisheries University
  • OHTA Hiromitsu
    Department of Ocean Mechanical Engineering, National Fisheries University

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Other Title
  • 105 並列型自己回帰モデルの性質に着目した船外機の状態監視手法(セッション1 モデル解析・設計)

Abstract

The fault diagnosis by acoustic signals on reciprocal engine is more difficult than independent mechanical elements, because almost reciprocal engine is composed of great number of structural bodies and mechanical elements. Reciprocal engine find it hard to identify of fault elements to exist a number of noise sources within the engine. This paper experimentally examines the possibility of diagnose fault conditions about a four stroke outboard marine engine based on generated acoustic signals measured by two microphones. Artificially assumed fault condition in the outboard engine is concerning intake and exhaust valve spring. Identification of above the fault conditions has been carried out based on cross correlation function of close two points signals and paralleled ARX model (Auto Regressive with Extra Input) at diagnosed location within the engine. It is possible to diagnose above fault condition by the proposal SN ratio improvement method.

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