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Incrementally accumulated holographic SDP characteristic fusion method in ship propulsion shaft bearing fault diagnosis

Xuewei Song, Zhiqiang Liao, Hongfeng Wang, Weiwei Song, Peng Chen

2021Measurement Science and Technology16 citationsDOI

Abstract

Abstract To improve the accuracy of the fault diagnosis of a ship propulsion shaft bearing in a harsh working environment, a visual diagnosis method based on the incrementally accumulated holographic symmetrical dot pattern (SDP) characteristic fusion method is proposed in this research. The current study simultaneously extracts the time- and frequency-domain characteristic parameters of a vibration signal based on the incremental accumulation method to avoid the inconspicuous difference and small discrimination generated by a single parameter. Subsequently, the extracted characteristic signals are transformed into a 2D image based on the SDP method to enhance the differences between signals. Eventually, bearing fault is diagnosed based on the similarity recognition method. Simulation and engineering experiments were conducted to verify the effectiveness of the proposed method. The results demonstrate that the proposed method can effectively diagnose the ship propulsion shaft bearing fault diagnosis.

Topics & Concepts

Bearing (navigation)PropulsionFault (geology)SIGNAL (programming language)VibrationComputer scienceSimilarity (geometry)HolographyFrequency domainArtificial intelligenceFusionTime domainControl theory (sociology)Pattern recognition (psychology)Image (mathematics)Computer visionEngineeringAcousticsGeologyAerospace engineeringPhysicsOpticsPhilosophyProgramming languageLinguisticsSeismologyControl (management)Machine Fault Diagnosis TechniquesFault Detection and Control SystemsAdvanced Measurement and Detection Methods
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