In order to monitor the wind turbine gearbox running state effectively, a fault diagnosis method of wind turbine gearbox is put forward based on wavelet neural network. Taking a 1.5 MW wind turbine gearbox as the target of study, the frequency spectrum of vibration signal and the fault mechanism of driving part are analyzed, and the eigenvalues of the frequency domain are extracted. A wavelet neural network model for fault diagnosis of wind turbine gearbox is established, and wavelet neural network is trained by using different feature vectors of fault types. The relationship between fault component and vibration signal is identified, and the vibration fault of wind turbine gearbox is predicted and diagnosed by network model. The analysis results show that the method can diagnose fault and fault pattern recognition of wind turbine gearbox very well.
The research on the propagation of surface waves has received considerable attention in order to improve the efficiency and natural life of the surface acoustic wave devices, but the investigation on complex Rayleigh waves in functionally graded piezoelectric material (FGPM) is quite limited. In this paper, an improved Laguerre orthogonal function technique is presented to solve the problem of the complex Rayleigh waves in an FGPM half-space, which can obtain not only the solution of purely real values but also that of purely imaginary and complex values. The three-dimensional dispersion curves are generated in complex space to explore the influence of the gradient coefficients. The displacement amplitude distributions are plotted to investigate the conversion process from complex wave mode to propagating wave mode. Finally, the curves of phase velocity to the ratio of wave loss decrements are illustrated, which offers extra convenience for finding the high phase velocity points where the complex wave loss is near zero.
In this study, low temperature deoxidization of lignin at temperature range of 200~390°C as a pretreatment method had been exploited to gain high quality pyrolysis products. A two-dimensional infrared correlation spectroscopy (2D-PCIS) was used to analyze the evolution of the functional groups of lignin in the process of low temperature deoxidization, and the deoxidized samples were pyrolysed in the pyrolysis gas chromatography mass spectrometry (Py-GC/MS). The results of 2D-PCIS showed that the decomposition of the lignin was accelerated from 320 °C and which was dominated by the elimination reaction. Notably, aromatization reaction was intensified at 350 °C, whereas the structure of lilac aromatic ring was more stable than the guaiac aromatic. It was also found that the alcohol hydroxyl group was significantly removed, and due to this removal other functional groups also underwent changes during the deoxidization. The results from Py-GC/MS experiments showed that deoxidization treatment at lower than 230 °C had insignificant effect on the pyrolysis products. However, when the deoxidization temperature was at 230°C and above, the oxygen-containing compounds in the pyrolysis liquid products (mainly phenols) decreased significantly, and when the deoxidization temperature was above 290 °C, hydrocarbons were the main compounds in the pyrolysis liquid product.
Coal plow is one of the important equipment for thin seam mining, it is very important to improve the performance of plow for efficient coal mining. In order to study the cutting performance of the coal plow, the cutting test is carried out in National Energy Mining Equipment Research Center, and the forces of the plow bit with different cutting speeds and depths are obtained. According to the properties of simulated coal wall, the intrinsic parameters of coal wall material are determined, and the three-dimensional bond contact model of coal wall is established by EDEM software. The force information of coal plow, the distribution of coal particles and the residual state of the coal wall surface are obtained through the numerical simulation. The results show that the maximum error of the force obtained by DEM simulation and experiment is 7.849 %, and the error of the width the residual coal ridge is 6.5 %. The force distribution of the plow bit is analyzed by combining the discrete element method with the finite element method. The high dynamic stress area of the plow bit is mainly concentrated in the back of the body and the alloy head inlay position. In order to reduce the consumption of the plow bit, local heat treatment is carried out on the plow bit, which can improve the mechanical properties of the plow bit. The simulation results are verified by experiments and industrial production, which proves the accuracy and feasibility of using DEM to study the cutting performance of coal plow.
The complex Rayleigh waves play an important role in the energy conversion efficiency of magneto-electro-elastic devices, so it is necessary to explore the wave propagation characteristics for the better applications in engineering. This paper modifies the Laguerre orthogonal polynomial to investigate the complex Rayleigh waves propagating in nonhomogeneous magneto-electro-elastic half-spaces. The improved method simplifies the calculation process by incorporating boundary conditions into the constitutive relations, shortens the solving time by transforming the solution of wave equation to an eigenvalue problem, and obtains all wave modes, including real and imaginary and complex wavenumbers. The three-dimensional curves of full frequency spectrum and phase velocities are presented for the better description of the conversion from complex Rayleigh wave modes to real wave ones; besides, the displacement distributions, electric and magnetic potential curves are obtained in thickness and propagation directions, respectively. Numerical results are analyzed and discussed elaborately in three cases: variation of nonhomogeneous coefficients, absence of magnetism, and absence of electricity. The results can be used to optimize and fabricate the acoustic surface wave devices of the nonhomogeneous magneto-electro-elastic materials.
Under the premise that the instantaneous speed can be accurately measured or precise estimated, order tracking is considered to be a classical and effective technique for non-stationary vibration analysis of rotating machinery. The meshing frequency components of the vibration signal measured from complex gearbox system interfere with each other mutually. The energy centrobaric correction method exhibits exact instantaneous frequency estimation (IFE) ability under the interference, but is susceptible to strong noise. Combining with time-varying filter and energy centrobaric correction method, a tacholess order tracking technique for gear fault diagnosis under the rotating frequency multi-linear fluctuation is proposed. The time-varying filter is designed to filter the strong noise signal, and then IFE could be accurately calculated from the filtered signal by energy centrobaric correction method. The instantaneous phase of reference shaft based on the Vold-Kalman filter (VKF) is used for angular resampling of the original vibration signal. The results show that the shaft rotating speed could be accurately identified from extracted gear meshing components. The order spectrum obtained by the proposed method with tacholess is substantially the same as the order spectrum obtained by a tachometer. Simulation analysis and experimental results verify the advantages of proposed tacholess order tracking technology for monitoring and fault diagnosis of gearbox vibration under the condition of strong noise and large speed variation.
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