Multi-Band Spectral Subtraction Method for Electrolarynx Speech Enhancement

Fault Diagnosis of a Helical Gearbox Based on an Adaptive Empirical Wavelet Transform in Combination with a Spectral Subtraction Method

Fault characteristic extraction is attracting a great deal of attention from researchers for the fault diagnosis of rotating machinery. Generally, when a gearbox is damaged, accurate identification of the side-band features can be used to detect the condition of the machinery equipment to reduce financial losses. However, the side-band feature of damaged gears that are constantly disturbed by strong jamming is embedded in the background noise. In this paper, a hybrid signal-processing method is proposed based on a spectral subtraction (SS) denoising algorithm combined with an empirical wavelet transform (EWT) to extract the side-band feature of gear faults. Firstly, SS is used to estimate the real-time noise information, which is used to enhance the fault signal of the helical gearbox from a vibration signal with strong noise disturbance. The empirical wavelet transform can extract amplitude-modulated/frequency-modulated (AM-FM) components of a signal using different filter bands that are designed in accordance with the signal properties. The fault signal is obtained by building a flexible gear for a helical gearbox with ADAMS software. The experiment shows the feasibility and availability of the multi-body dynamics model. The spectral subtraction-based adaptive empirical wavelet transform (SS-AEWT) method was applied to estimate the gear side-band feature for different tooth breakages and the strong background noise. The verification results show that the proposed method gives a clearer indication of gear fault characteristics with different tooth breakages and the different signal-noise ratio (SNR) than the conventional EMD and LMD methods. Finally, the fault characteristic frequency of a damaged gear suggests that the proposed SS-AEWT method can accurately and reliably diagnose faults of a gearbox.

Design and Evaluation of a Mechanically Driven Artificial Speech Device

This paper presents the design of a mechanically driven artificial speech device to be used by laryngectomees as an affordable alternative to an electrolarynx (EL). Design objectives were based on feedback from potential end users. The device implements a mainspring powered gear train that drives a striker. The striker impacts a suspended drum-like head, producing sound. When pressed against the neck, the head transmits sound into the oral cavity, allowing the user to produce intelligible speech. The dynamics of the vibrating head and sound pressure levels (SPLs) produced at the mouth were measured to compare performance between the device and a common, commercially available EL. The results showed comparable performance and sound output.