Study on Dynamic Characteristics and Parameter Influence of a Kind of Bilateral Restraint Impact Vibration System

In this paper, the hinge in the articulated structure is studied, the gap hinge is described as a nonlinear bilateral constraint, and the equivalent modeling and analysis of the hinge connection collision vibration are carried out based on the Lankarani–Nikravesh nonlinear contact force model. With the help of the method of nonlinear system dynamics analysis research, the Poincaré mapping of hinge joint collision vibration is constructed, the bifurcation diagram of the system with different parameters is solved, and the variation law of the system motion and the influence of parameters are analyzed by combining the time response diagram, phase diagram, Poincaré cross section diagram, and spectrum diagram of the typical motion of the system. The simulation results show that the system moves in a single degree of freedom and varies with parameters with multiplicative period bifurcation and rubbing edge bifurcation leading to chaos; the system’s periodic motion has shock state mutation and mirror jump transformation.

Tahe effect of spring coefficients in the dynamic analysis model of the pile foundation structure in Binh Thuan seas, Vietnam

Now, the field experiments according to the non-destructive test method are developing widely in diagnostics and verification of structural engineering. To research and apply the impact vibration test, one of these non-destructive methods, the construction of the design dynamic analysis model is significant. The paper goes into research on the formulas to determine the dynamic spring coefficients according to Japanese and Vietnamese standards. Then, apply calculations for dynamic analysis models of pile foundations built in the Binh Thuan sea area. The impact vibration test in the field shows the appropriate formula for calculating the coefficient of dynamic springs in Binh Thuan, Vietnam.

Nonlinear vibration of a buckled/damaged BNC nanobeam transversally impacted by a high-speed C60

Nanotube can be used as a mass sensor. To design a mass sensor for evaluating a high-speed nanoparticle, in this study, we investigated the impact vibration of a cantilever nanobeam being transversally collided by a high-speed C60 at the beam's free end with an incident velocity of vIn. The capped beam contains alternately two boron nitride zones and two carbon zones on its cross section. Hence, the relaxed beam has elliptic cross section. The vibration properties were demonstrated by molecular dynamics simulation results. Beat vibration of a slim beam can be found easily. The 1st and the 2nd order natural frequencies (f1 and f2) of the beam illustrate the vibration of beam along the short and the long axes of its elliptic cross section, respectively. f2 decreases with increasing temperature. A minimal value of vIn leads to the local buckling of the beam, and a different minimal vIn leading to damage of the beam. For the same system at a specified temperature, f2 varies with vIn. When the beam bends almost uniformly, f2 decreases linearly with vIn. If vIn becomes higher, the beam has a cross section which buckles locally, and the buckling position varies during vibration. If vIn approaches the damage velocity, a fixed contraflexture point may appear on the beam due to its strong buckling. Above the damage velocity, f2 decreases sharply. These results have a potential application in design of a mass sensor.

Vibration Detection of Vehicle Impact Using Smartphone Accelerometer Data and Long-Short Term Memory Neural Network

Vehicle's analysis can be useful for a variety of traffic problems, such as monitoring road damages and vehicle type classification. Further, traffic behavior analysis can be useful to monitor traffic jams as a smart cities solution. In this paper, the vibration caused by a vehicle passing through a speed bump was recorded with a docked smartphone. The acquired signals were processed in order to detect the generated impact. In order to analyze this data a LSTM neural network was used due to its classification process over time while the smartphone accelerometer was continuously operating (waiting for a vehicle pass by). This deep learning technique allows the use of raw 3-axis accelerometer data. The results achieved 98% of accuracy with a low level of false positives (less than 1%). Indicating that the methodology is effective in classification of vehicles by their impact vibration.