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Improved design of Tc bearing structure used for measurement while drilling
Get PDFThis paper focuses on the improved design of Tc bearing’s structure form. A sand transmission groove is designed around the outer ring of Tc bearing to make it easy to remove solid particles, and the dynamic pressure Reynolds equation of Tc bearing is solved and the static characteristics of two structures of Tc bearing are compared and analyzed. Overall, conclusions are drawn: the carrying capacity of Tc bearing with the sand transmission groove is less than that of the original Tc bearing; the end discharging capacity of Tc bearing with the sand transmission groove is more than that of the original Tc bearing, which is in favor of the removal of solid particles from the Tc bearing and the enhancement of sand removal function; improving the dynamic characteristics of the liquid film of Tc bearing, Tc bearing with the sand transmission groove is suitable for the rotor system with high-speed light-load of MWD
Dynamic analysis and control of strip mill vibration under the coupling effect of roll and rolled piece
Get PDFAccording to the “Hill rolling force formula”, taking particular account of the influence from horizontal vibration of rolled piece in roll gap, a dynamic rolling force model is analyzed. Considering the interaction between vibration of strip and roll, the dynamic vibration model of rolling mill is established. On this basis, the time delayed feedback is introduced to control the vibration of the roll system. The amplitude frequency response of the coupled vibration control equation is obtained by using the multiple scales method. Different time delay parameters are selected to test the control effect. Research results show that the unstable vibration of the roll system can be suppressed with appropriate time delay feedback parameters. Because it is simpler and has good control effect in solving nonlinear mechanical vibration, so these results will make a difference for the research of strip mill vibration, and provide theoretical basis for strip steel production
Application of deterministic resampling particle filter to fatigue prognosis
Get PDFThe method based on a particle filter for a fatigue crack growth prognosis has proved to be a powerful and effective tool for developing prognostics and health management (PHM) technology. However, the widely used basic particle filter have the unavoidable particle impoverishment problem, which will make particles unable to approximate the true posterior probability density function of the system state and lead to a prognosis result with a large error. This paper proposes a fatigue crack growth prognosis method based on a deterministic resampling particle filter. The active structural health monitoring based on the Lamb wave is used for on-line crack length monitoring with piezoelectric transducers. With the on-line crack measurement, the crack state and crack growth model parameters are estimated for a fatigue crack growth prognosis. In addition, the deterministic resampling procedure is employed to overcome the particle impoverishment problem. The result shows the proposed crack growth prognosis method based on deterministic resampling particle filter can provide more satisfactory results than the basic particle filter
Three-dimensional operational modal analysis based on self-iteration principal component extraction and direct matrix assembly
Get PDFThis paper proposes a self-iteration principal component extraction (SIPCE) and direct matrix assembly method for three-dimensional structures. Different from calculating principal components (PCs) by matrix decomposition in traditional principal component analysis (PCA), SIPCE extracts PCs one by one through self-iteration, so SIPCE has lower space-time complexity. Besides that, it avoids singular-value and ill-posed problems of matrix decomposition. The previous method of solving three-dimensional structures is using modal coordinate response back general reversion of least square algorithm, while the new matrix assembly method calculates three-dimensional modal shapes at one time. So, the new matrix assembly method has less calculation error. The numerical simulation results in a cylindrical shell demonstrate that this method can be practically and effectively applied in operational modal analysis (OMA) of three-dimensional structures. The new method is also robust to noise, and has higher identification accuracy and lower space-time consumption than previous method
Active vibration isolation using a six-axis orthogonal vibration isolation platform with piezoelectric actuators
Get PDFPiezoelectric actuators (PEA) act an important role in active vibration control area due to the advantages of fast response, high output force, small size and light weight. A 6-axis orthogonal vibration isolation platform based on PEAs is designed, which satisfies the demands of heavy payload, small installation space and multi degree of freedom vibration isolation. The dynamic model of the six-axis orthogonal vibration isolation platform with PEAs is established using Newton-Euler method. With the layout of six PEAs around the axis of symmetry, the dynamic equations could be decoupled into two single-input-single-output (SISO) subsystems and two multi-input-multi-output (MIMO) subsystems. Based on the modal superposition method, the two MIMO subsystems are further decoupled. The control strategy for each SISO system is developed with LQR control method. To evaluate the effectiveness of the control method, the simulation and verification experiment are conducted. The simulation result and experimental data indicate that the decoupling control of the proposed six-axis orthogonal vibration isolation platform with piezoelectric actuators effectively reduces the vibration response of payload within the target frequency range of 20 Hz to 200 Hz
The effect of lubricant inertia on fluid cavitation for high-speed squeeze film dampers
Get PDFThis work studies the effect of lubricant inertia on the fluid cavitation for partially sealed high-speed squeeze film dampers (SFDs) executing small amplitude circular-centered orbits (CCOs). The lubricant cavitation is modeled by both the Elrod algorithm and the Gumbel’s cavitation boundary condition to provide the comparison between the most common lubricant cavitation models. Additionally, the fluid inertia is integrated by adapting a finite-length SFD model for partially sealed dampers. The integrated SFD model is incorporated into a numerical simulation model and the results are validated by comparison with experimental data. The results of the analysis demonstrate that the fluid inertia effects significantly extend the cavitation region and influence the cavitation onset and the film reformation
Free vibration of square plate with temperature effect
Get PDFIn modern engineering, researchers/scientists are very keen to know first few modes of vibration because it provides how system/structure behaves under vibration. In this paper, author computed the natural vibration of non homogeneous tapered square plate. Here tapered means that plate’s thickness varies linearly along x-axis. Here non homogeneity arises in the plate’s material due to simultaneous variation in density (circular variation) and Poisson’s ratio (exponential variation). Temperature variation on the plate is viewed bi-parabolic along the axes. Rayleigh-Ritz technique is applied to obtain the frequency equation and vibrational frequency modes under different combination of parameters. The findings of the papers are presented in tabular form
A novel intelligent fault diagnosis method of rotating machinery based on deep learning and PSO-SVM
Get PDFA novel intelligent fault diagnosis method based on deep learning and particle swarm optimization support vectors machine (PSO-SVM) is proposed. The method uses deep learning neural network (DNN) to extract fault features automatically, and then uses support vector machine to classify diagnose faults based on extracted features. DNN consists of a stack of denoising autoencoders. Through pre-training and fine-tuning of DNN, features of input parameters can be extracted automatically. This paper uses particle swarm optimization algorithm to select the best parameters for SVM. The extracted features from multiple hidden layers of DNN are used as the input of PSO-SVM. Experimental data is derived from the data of rolling bearing test platform of West University. The results demonstrate that deep learning can automatically extract fault feature, which removes the need for manual feature selection, various signal processing technologies and diagnosis experience, and improves the efficiency of fault feature extraction. Under the condition of small sample size, combining the features of the multiple hidden layers as the input into the PSO-SVM can significantly increase the accuracy of fault diagnosis
Adopting method of key block and energy distribution to predict the slope stability under blasting
Get PDFAt present, an important slope stability analysis method consists in the evaluation of the bearing capacity of key block, which is located between the joints and fissures in rock mass, and plays the decisive role on the slope stability. Because of the defective equivalent accuracy and elusory mechanical path, the traditional analysis methods have some inevitable errors. However, the energy theory can avoid the above defects easily, in this paper, the analytical input energies are potential energy and blasting vibration energy, and the consumed energies are fractured dissipative energy, friction dissipative energy and kinetic energy of instability. In order to eliminate the size effect problem, it is necessary to emphasize each part of energy expression as the energy density form. And the first four items would be confirmed by different theories and tests, so that the instability kinetic energy could be evaluated by the energy conservation law, and then the instability velocity could be calculated to predict the instability grade of slope
Lifting load monitoring of mine hoist through vibration signal analysis with variational mode decomposition
Get PDFMine hoists play a crucial role in vertical-shaft transportation, and one of the main causes of their faults is abnormal lifting load. However, direct measurement of the load value is difficult. Further, the original structure must be destroyed for sensor installation. To facilitate efficient and accurate monitoring of the lifting load of mine hoist, this paper presents a novel condition-monitoring method based on variational mode decomposition (VMD) and support vector machine (SVM) through vibration signal analysis. First, traditional empirical mode decomposition (EMD) is used to analyze the vibration signal collected by an acceleration sensor, and the number of obtained intrinsic mode functions (IMFs) is employed to set the VMD mode number. Second, the obtained vibration signal is processed by the parameterized VMD, and the useful IMFs of VMD are selected through correlation analysis for feature extraction. Third, the obtained features are used to train an SVM model, and the trained SVM is used to monitor the mine-hoist lifting load. In this study, experiments on an operated mine hoist are also conducted to verify the reliability and validity of the proposed method. The experimental results show that the proposed method can accurately identify the considered lifting load conditions