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Adaptive empirical Fourier decomposition (AEFD) is a recently developed approach of nonstationary signal mode separation. However, it requires to set the spectrum segmentation boundary relying on the users' professional experience ahead of time. In this paper, a novel spectral envelope-based adaptive empirical Fourier decomposition (SEAEFD) method is proposed to improve the performance of AEFD for rolling bearing vibration signal analysis. In the proposed SEAEFD approach, fast Fourier transform (FFT) of the raw signal is calculated to obtain the frequency spectrum at first. Then, the spectral envelope processing is implemented on the spectrum signal obtained by FFT to achieve an adaptive segmentation. In the traditional segmentation method, generally, the minima and midpoints between adjacent extreme points are taken as the spectrum segmentation boundary, in which the obtained frequency band contains more interference components. To achieve the effect of denoising and restrain the noise that existed in the collected vibration signal, SEAEFD is proposed to optimize the spectrum segmentation boundary so that the obtained frequency band contains the least noise components. Lastly, the inverse FFT is used to reconstruct the component signal within each frequency band and the gained signals are termed as Fourier intrinsic mode functions (FIMFs). Therefore, SEAEFD enables a nonstationary signal to be decomposed into several single-component signals with instantaneous frequencies of physical significance. The proposed SEAEFD method is compared with recently developed methods, including EAEFD, AEFD, EWT, VMD and EMD methods, by analyzing the simulation signals and the measured data of rolling bearing. The results indicate that SEAEFD is valid in diagnosing rolling bearing faults and gets a better diagnosis performance than the compared methods.

At present, China’s energy distribution and economic development are extremely unbalanced. In order to make rational use of resources, China has promoted the “west to East power transmission” and “north to South Power Transmission” pattern. HVDC transmission has obvious advantages in this long-distance transmission, but there are some shortcomings in the traditional LCC-HVDC system. Therefore, a new system LCL-HVDC is proposed. Firstly, some advantages of the system are introduced; secondly, LCC-HVDC and LCL-HVDC models are built in Simulink, in which the current distortion rate of valve side winding of converter transformer is measured; finally, compared with LCC-HVDC, the loss of LCL-HVDC converter transformer is studied by using method 2 recommended by IEEE standard, and the kn value of the new system is calculated.

(Li1+, Al3+) co-doped Ni0.5Zn0.5Fe2O4 ferrites, Ni0.5-xZn0.5-xLixAlxFe2O4 (x = 0.000, 0.025, 0.050 and 0.100), were synthesized by the sol-gel auto-combustion method. X-ray diffraction (XRD), field emission scanning electronic microscope (FESEM), vibrating sample magnetometer (VSM) and LCR meter were used to investigate the structural, magnetic and dielectric properties. Results of XRD and SEM indicate that both doping amount and calcination temperature play significant roles in crystal structure and grain growth. Also, it can be observed that the saturation magnetization and the coercivity change in a noticeable manner. The Ni0.475Zn0.475Li0.025Al0.025Fe2O4 ferrite sintered at 1200 °C has a relatively low coercivity value (62.93 Oe) and the largest saturation magnetization (110.95 emu/g). Besides, dielectric behavior is also improved by Li1+ and Al3+ co-doping.

(Li1+, Zn2+ and La3+) co-substituted NiFe2O4 ferrite ceramics (Ni0.8-xZnxLi0.1La0.1Fe2O4, x = 0.0, 0.2, 0.4, 0.6, 0.8) were prepared by the sol-gel auto-combustion method. The structural properties were investigated by X-ray diffraction and field emission scanning electronic microscope techniques. Vibrating sample magnetometer and LCR meter were used to probe magnetic and dielectric properties. A relatively high value of saturation magnetization (105.94 emu/g) can be achieved in Ni0.4Zn0.4Li0.1La0.1Fe2O4 sample sintered at 1100 °C. In addition, the soft magnetic properties are also enhanced due to a reduced coercivity value. Also, dielectric behavior is improved and all the results show that co-substitution with Li1+, Zn2+ and La3+ ions as well as modulation via Zn2+ ions has a great impact on the properties of Ni ferrites.

This work performs a detailed theoretical analysis for low-concentration solar thermophotovoltaic (STPV) system with both solar absorber and thermal emitter made of previously-developed selective metafilms along with a cavity reflector for performance enhancement. When paired with an InGaAsSb cell, the initial metafilm structure shows an STPV system efficiency of 7.1% at 50 suns, where about half of the incident solar energy is lost through the thermal emission from the top surface of the absorber according to energy loss analysis. In order to enhance the STPV system performance, the metafilm layer thicknesses of the solar absorber and those of the thermal emitter are optimized at 50 suns, increasing the STPV system efficiency from 7.1% to 10.2%. Moreover, a cavity reflector above the absorber is considered to recycle the infrared photons emitted from the top surface of the absorber. The effects of the size and the reflectivity of the cavity reflector on the efficiency are discussed. The results show that, the efficiency of the optimized metafilm based STPV system at 50 suns can be increased from 10.2% to 17.4% with a cavity made of ideal reflectors.

Anaerobic ammonium oxidation (anammox) is carbon friendly biological nitrogen removal process, and recently more focus is given to improving the anammox activity. Because of its high adsorption and modifiability, graphene and its derivative in wastewater treatment have received much attention. However, the specific effects and mechanisms of graphene oxide (GO) and reduced graphene oxide (RGO) on anammox are still controversial. Extensive data analysis was performed to explore the effects of GO and RGO on anammox. Statistical analysis revealed that 100 mg/L GO significantly promoted the anammox process, while 200 mg/L of GO inhibited the anammox process. The promotion of anammox performance under the influence of RGO was dependent on the temperature. The Logistic model was utilized for depicting the variation of nitrogen removal efficiency under promoting dosage of graphene oxides. A neural network model-based analysis was performed to reach anammox's potential mechanisms under the influence of two graphene oxides. Spearman correlation analysis showed that GO and RGO had significant positive correlations with nitrogen removal efficiency and specific anammox activity (p 0.01), especially for RGO. In addition, the abundance of Planctomycetes and Nitrospirae was positively correlated with the addition of graphene oxides. This work comprehensively unraveled the role of graphene oxide materials on the anammox process and provided practical directions for the enhancement of anammox.

The gearbox is a vital component for rotating machinery and has been used in many critical engineering applications. Surface wear is a common but inevitable phenomenon during the lifespan of the gearbox. Its propagation can result in some catastrophic failures and cause unexpected economic loss. Therefore, it is vital to evaluate the degradation process of the gear system caused by surface wear propagation in order to make reliable predictive maintenance-based decisions to ensure the safe operation of the gearbox transmission system. The vibration analysis technique is a prevailing tool for rotating machine condition monitoring. However, research on vibration-based gear wear monitoring is relatively rare as the dynamic interactions between gear surface wear and gear system dynamic characteristics would produce complex gear dynamic responses and vibration features. Therefore, this paper presents a novel similarity-based status characterization methodology for gear wear monitoring. In this proposed methodology, a novel gear wear monitoring indicator is developed to evaluate gear tooth contact characteristics at different wear severities, which could significantly benefit gear systems' health management. The effectiveness of the proposed method for gear wear propagation process monitoring is presented and proven through a series of run-to-failure tests with different lubrications and operational conditions.