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In order to effectively capture the fault features contained in the vibration signals of the rotating machinery and complete the fault diagnosis task efficiently, a fault diagnosis model combining two-dimensional image features and lightweight neural network is designed. Firstly, the collected one-dimensional vibration signals are decomposed by modified ensemble empirical mode decomposition (MEEMD) to obtain the intrinsic mode function (IMF) components, and the corresponding IMF components are selected for sum reconstruction to enhance the amplitude fluctuation of vibration signals. Then, Markov transition field (MTF) could be used to more effectively characterize the fault features in the reconstructed signals. Secondly, the 2D feature map generated by MTF is input into residual depth separable convolutional neural network (ResDSCNN) for feature extraction and fault diagnosis. The planetary gearbox fault data set is used to verify the performance of the model, and the results show that the diagnosis accuracy of the model for all kinds of gear faults can reach more than 98%.

A new kind of compound extrusion technology including direct extrusion and shears for AZ31 magnesium billets can cause plastic large deformations and high strain rates. A series of compressive tests have been done to obtain the stress-strain curves of AZ31 magnesium alloy. Three-dimensional (3D) thermo-mechanical coupled finite element modeling of forming magnesium alloy AZ31billets into small rods at certain high ram speed and low temperature by extrusion-shears have been carried out. The simulation model has been established and meshed based on symmetrical characteristic. Computed parameters including material characteristics for workpiece and die and process conditions consisting of initial billet temperature, extrusion ratio, channel angle and ram speed have been list. The evolution of temperature during extrusion-shear process, there are hardly any temperature gradients within the workpiece, but temperature in severe plastic deformation zone increase rapidly. Strain evolutions for inner billet are larger than those of border positions. The flow velocity distribution is uniform basically which avoid the extrusion cracks to a certain degree. Experiments show that the rods with good surface smoothness can be obtained by low temperature and high speed extrusion-shear, and the alloy grains are effectively refined by dynamic recrystallization (DRX).

To explore the deformation mechanisms of a new composite extrusion including extrusion and successive shear subsequently which is shorten "ES", Three dimensional finite element modeling of grain refinements for magnesium alloys by ES process has been researched. The ES die have been designed and manufactured and installed to the horizontal extruder. Finite element software DEFORM TM-3D to investigate the plastic deformation behaviors of magnesium alloy during extrusion-shear has been employed. The extrusion loads and temperatures distribution of billets and maximum extrusion forces have been obtained from simulation results. From the simulation results it is clear that evolutions of extrusion loads curve and effective stresses and temperatures can be divided into three stages. ES process has been applied to fabricate AZ31 magnesium alloy rod at preheat temperature of 420ºC with extrusion speed of 20 mm/s. The results proved that the ES process is a formality method for magnesium suitable for large scale industrial application. The microstructures of AZ31 magnesium alloy along the longitudinal section of rods have been sampled and examined and observed. Fine grained microstructures can be observed throughout longitudinal section of extruded rod. The researches results show that ES process would cause severe plastic deformation and improve the dynamic recrystallization of AZ31 magnesium alloy. The simulation results and calculated Zener-Hollomon parameters showed that the grains of magnesium would be refined gradually during ES process.

Summary: This paper presents an analog tracking bandpass filter that is intended to be applied in ac signal acquisition circuits to reduce measurement noise. A fast and accurate frequency tuning technique is developed based on the phase control loop. A complete derivation process is provided to build the mathematical model describing the control loop for the tracking filter. Accordingly, a zero‐crossing detector is designed to accurately extract signal phases in the proposed loop. As a closed‐loop control system, the loop dynamics such as stability, transient response, and steady‐state error are analyzed using the derived model. From both the simulations and measurements, the developed filter is found to provide excellent performance in frequency tracking, noise reduction, and linearity compared to existing work. The maximum and minimum Q value reaches 42.2 and 14, respectively, in the frequency tuning range of 34 to 107 kHz, while the frequency tracking error is less than 1.18% at 100 kHz. [ABSTRACT FROM AUTHOR]