Fatigue cracks generated during operation would alter the aero-engine blade vibration characteristics, manifested as frequency veering and mode shape switching. Study on the frequency veering can lead us to a further understanding of the blade crack evolution process. After building the FEM of aero-blade, the influence of crack parameters (crack location and length) on blade natural vibration and forced vibration characteristics was studied based on structural modal vibration theory, focusing on the variation laws of vibration frequency and mode shapes in the frequency veering area. The research shows that crack location and length variation would affect the blade frequencies and mode shapes, and thus lead to complex frequency veering, mode coupling and mode shape switching characteristics, which explains why mode shapes alter with the crack length and location in the same vibration mode.
The focus of this paper is to analysis the fracture and damage characterize of reinforced concrete (RC) column subject to dynamic and static loading based on acoustic emission (AE) technique. The multi-dimensional dynamic/static loading test of RC columns is conducted with the loading rate of 40mm/s and 0.1mm/s respectively. By b-value analysis, the moment of macro-crack opening is acquired, and by which, the ratio of macro-crack opening load to maximum load is proposed to evaluate the damage condition. In addition, the load condition and damage accumulative rate of RC column subject to both dynamic and static loading are analyzed. The results are shown that: the distribution of AE amplitude, which also can be seen as b-value, can capture the moment of macro-crack opening in RC column. The macro-crack subject to dynamic loading needs smaller external load compared with the one subjected to static loading. The dynamic loading is more likely to lead the formation of macro-crack. The time parameter of AE event accumulation can clearly reflect the damage accumulate rate of RC column. Moreover, the damage accumulate rate in high loading rate specimen is larger than the one in loading rate specimen. And the high loading rate is more easily to make and aggravate the structural damage.
The traditional independent component analysis is too difficult to solve the problems of underdetermined blind source separation(BSS) and statistically correlated sources separation existed in mechanical fault diagnosis.Assuming some sub-components of correlated machine vibration sources are independent,a novel blind source separation method based on subband extraction of ensemble empirical mode decomposition(EEMD) is proposed to solve the problem of single-channel statistically correlated mechanical signals separation. Firstly in this method,the single-channel signal is decomposed into a series of subband observed signals by ensemble empirical mode decomposition,then the number of source signals is estimated by singular value decomposition and Bayesian information criterion.Secondly,the new observed signals are reconstructed by the subband observed signals with high independence according to the mutual information criterion and the number of sources,the dimension of the new observed signal is increased.Finally,The source signals are estimated through the reconstructed observed signals by using whitening process and joint approximate diagonalization.The simulation and experiment testify the validity of the proposed method.
The working performance of smart actuators is affected by the hysteretic effect nonlinearity. Thus, it is necessary to identify and compensate the hysteresis nonlinearity to achieve precision motion. At first, based on the singular value decomposition (SVD) method, the parameters of the Preisach model are identified using the de-signed harmonic input signals with varying amplitudes to satisfy PE condition. Then, based on the identified Preisach model, the mode-inversion feedforward is designed to compensate the hysteresis nonlinearity. Finally, the piezoelectric stage is used to validate the proposed identification and compensation methods. The experimental re-sults indicate that the hysteresis nonlinearity has been identified using the SVD method, the tracking error has been reduced by 89.5% using the model-inversion compensator. The proposed identification and compensation ap-proaches have been verified.
The shield is widely used in underground projects. The cutting-tool wear of shield machine has become a key problem that affects the engineering quality and progress. Acoustic emission(AE) as a nondestructive detection method has been widely applied in all kinds of field. Acoustic emission signal which has rich multi feature information can reflect accurately the detection member state. In the study of acoustic emission signal, How to distinguish between effective signal characteristics of acoustic emission and how to use the characteristic information to evaluate is a hot research at home and abroad. Based on the comprehensive experiment platform of rock and machine, By acquisiting emission signal of different shield cutter wear, The adaptive filter and acoustic emission detection are applied to detect the field shield cutter and use information entropy multi feature fusion technology assessment. According to the state of the database tool wear information entropy and the corresponding can clearly understand the wear condition of shield cutter.
According to the dynamic similarity theory to design the reasonable scale model, take dynamic test analysis of the container crane structure by shaking table. In the scale model, the length of each component (beam) size can be based on the size of the prototype, but the cross-section thickness cannot change according to the same scale narrowed, causing distortion model. Finite element prediction coefficient method can get the prediction coefficient which using to the distortion model predict the dynamic characteristics of prototype. In order to verify the effectiveness of distortion coefficient that obtained by the finite element prediction coefficient method, made a distortion model that the thickness of the cross-section distorted and a hammering modal test and a series of seismic sharking table tests were successively carried out. The results showed that the experimental results similar to the calculation results, the maximum acceleration and strain in the same position, distortion coefficient of prediction is reasonable.
To improve the shock absorbing performance of UAV landing gear, dynamic analysis and optimization for a cushioning mechanism of articulated landing gear is performed. Firstly, based on the establishment of mathematic model of UAV ground movement and the stress analysis of landing gear when it is under braking control, the behavior and scheme of cushioning mechanism is discussed. Secondly, the software of multidisciplinary design optimization (iSIGHT) combined with the dynamic software(Adams) are applied to the optimization of cushioning mechanism. Then, by taking the requirements of braking condition and shimmy containment as constraint, the size of cushioning mechanism and the spring stiffness are optimized by using the method of point-by-point comparing at macrocosm combined with sequential quadratic programming method. Finally, the taxiing test and stiffness test for the optimal landing gear are carried out. The results show that the compression displacement meets the desired requirement and the efficiency of buffer is increased by 71.5%. The analysis and optimization method provide guidance for the design of UAV articulated landing gear.
The dispersion effect in the Hopkinson pressure bar high-g loading technique was caused by the lateral inertia motion of the particle, leading to an inaccurate acceleration in peak and duration. Based on the Fast Fourier Transform (FFT) approach, the dispersion effect was corrected. Then, acceleration pulses at different locations along the pressure bar were compared to check the dispersion effect. In addition, before and after dispersion correction, the acceleration pulses on the specimen were obtained under different pulse loading, and the errors of the peak and duration were analyzed. Results show that the acceleration pulses at different locations of the bar are different in peak and duration due to the dispersion effect, and the errors of the peak acceleration on the initiator are more than 10%. The errors of the acceleration duration depend on the pulse shape, but the absolute errors are all less than 6μs. As for the dispersive pulse, dispersion correction is a necessary procedure to obtain a more accurate acceleration pulse.
