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Wavelet transform is one of the most acceptable tools to analyze vibration signals for gear fault detection. However, there are still some limitations of the traditional wavelet transforms due to the utilization of fixed linear filters. This investigation presents an adaptive morphological gradient lifting wavelet (AMGLW) to remedy the shortcomings of traditional wavelet transform schemes. A novel nonlinear filter, named morphological gradient filter, is designed for enhancing the impulsive features of the original signal. Then the adaptability of AMGLW is implemented by selecting between two filters, namely the average filter and the morphological gradient filter, to update the approximation signal dependent upon the local gradient of the analyzed signal. This new scheme is evaluated on a simulated signal and a practical vibration signal measured from a gearbox. Experimental results demonstrate that the presented AMGLW outperforms the traditional linear wavelet (LW) transform obviously for detecting gear defects. Furthermore, the computational cost of AMGLW is much less than the traditional LW. Thus the AMGLW scheme is quite suitable for the online condition monitoring of gears.

In order to promote the practical application of the heterogeneous Fenton process in wastewater treatment, Fe3O4 nanoparticles were prepared and used to degrade organic pollutants efficiently over a wide pH range, using phenol as a model. During fabrication, the effects of Fe(2+)/Fe(3+) ratio and thermal treatment temperature were investigated and optimized. Using a transmission electron microscope and X-ray diffraction, the nanoparticles were found in the form of Fe3O4 with an average size of 15 nm. The effects of Fe3O4 nanoparticle concentration H2O2 concentration, and pH on the removal efficiency and chemical oxygen demand (COD) abatement efficiency of phenol were investigated. Under optimized conditions, the nano-Fe3O4 heterogeneous Fenton system could achieve phenol and COD removal efficiencies of 100 and 70% respectively. This nanocatalyst was observed to have a high efficiency at a wider pH range (2-9), and a possible mechanisms for this effect was proposed.

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