A Novel Fault Identification Method Using Modified Morphological Denoising via Structuring Element Optimization for Transmission Systems of Shipborne Antennas

Zipeng Li,Kunde Yang,Shunli Duan,Jinglong Chen

doi:10.3390/jmse10020190

Abstract

Unlike common rotating machines, shipborne antennas always work under variable loads and suffer from extreme ocean conditions, which makes monitoring their condition and early fault identification necessary and challenging. However, extracting weak fault characteristics from vibration signals accurately and efficiently is difficult because of multi-modulation phenomenon and heavy noise. Therefore, an adaptive denoising method based on morphological filtering via structuring element optimization is proposed in this paper. The proposed method mainly includes two aspects: an adaptive spectrum segmentation algorithm via scale expression and a criterion based on the characteristic energy ratio for structuring element optimization. Experimental signals and a set of comparisons verify the effectiveness and robustness of the proposed method. The proposed method is also applied to identify an early antenna drivetrain fault in a real case, showing its superiority and effectiveness.

Highlights

Shipborne antennas always suffer from severe ocean environments, such as salt spray, elevated temperatures and huge waves
Once a localized fault occurs on the surface of key components, such as bearings and gears, a series of periodic pulses will appear in the vibration monitoring signal because of the contact between the faults and their mating surfaces [11,12]
We focus on structure element (SE) optimization and propose a data-based SE optimization method to improve the performance of morphological filtering

Summary

Introduction

Shipborne antennas always suffer from severe ocean environments, such as salt spray, elevated temperatures and huge waves. Key components of the shipborne antenna drivetrain degenerate and are damaged inevitably after long-term operation, which may influence the pointing precision of the antenna and even cause marine perils [1,2]. Condition monitoring and fault alarms for shipborne antennas are necessary and have attracted great attention all over the world [3,4,5]. Many monitoring factors, including but not limited to vibration, acoustic signal, temperature and oil samples, are used to identify mechanical faults of key components [6,7]. Once a localized fault occurs on the surface of key components, such as bearings and gears, a series of periodic pulses will appear in the vibration monitoring signal because of the contact between the faults and their mating surfaces [11,12]. The core of antenna drivetrain fault detection is noise reduction and fault feature extraction

Objectives

Methods

Conclusion