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Abstract

This paper demonstrates the use of a zinc oxide (ZnO) thin film in a 1-μm ring laser cavity as a saturable absorber to successfully generate Q-switching pulses. The tunability of the laser pulses is achieved by integrating a tunable bandpass filter (TBPF) in an ytterbium-doped laser cavity that results in 9.4 nm of tuning range, which wavelength is from 1040.70 nm to 1050.1 nm. The peak energy in the pulse which is 1.47 nJ was measured together with a minimum pulse width of 2.4 μs. In addition, the repetition rate increases from 25.77 to 45.94 kHz as the pump power level being increased from 103.1 to 175.1 mW. The results obtained in this experiment demonstrated consistent results and stable throughout the experiment. Therefore, ZnO thin film is considered as a good candidate in 1-μm pulsed laser applications.

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Authors and Affiliations

R.A. Shaharuddin
S.A. Azzuhri
M.A. Ismail
F.A.A. Rashid
M.Z. Samion
M.Z.A. Razak
H. Ahmad
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Abstract

Rotating element bearings are the backbone of every rotating machine. Vibration signals measured from these bearings are used to diagnose the health of the machine, but when the signal-to-noise ratio is low, it is challenging to diagnose the fault frequency. In this paper, a new method is proposed to enhance the signal-to-noise ratio by applying the Asymmetric Real Laplace wavelet Bandpass Filter (ARL-wavelet-BPF). The Gaussian function of the ARLwavelet represents an excellent BPF with smooth edges which helps to minimize the ripple effects. The bandwidth and center frequency of the ARL-wavelet-BPF are optimized using the Particle Swarm Optimization (PSO) algorithm. Spectral kurtosis (SK) of the envelope spectrum is employed as a fitness function for the PSO algorithm which helps to track the periodic spikes generated by the fault frequency in the vibration signal. To validate the performance of the ARL-wavelet-BPF, different vibration signals with low signal-to-noise ratio are used and faults are diagnosed.
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Authors and Affiliations

Muhammad Ahsan
1
ORCID: ORCID
Dariusz Bismor
1
ORCID: ORCID
Muhammad Arslan Manzoor
2

  1. Department of Measurements and Control Systems, Silesian University of Technology, 44-100 Gliwice, Poland
  2. Department of Natural Language Processing, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE

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