Acoustic Emission (AE) technique is one of the nondestructive methods to evaluate the size, location and generation time of deformation or damage of material in real times. Generally AE sensors are directly attached on the surface of the component to detect AE wave, however this method brings about inconvenient setting to many industrial processes. In the present study, an arrangement of AE sensors was investigated to monitor laser shock peening (LSP). Instead of direct attachment of the sensors on the target, several AE sensors were located in the water layer to detect acoustic wave propagating through the water. The results showed that the sensor arrangement has a good performance to monitor LSP. Impact pressures during LSP process were obtained from detected AE waveforms by deconvolution technique. In addition, with AE measurement, sample surface was observed by high speed camera and investigated phenomena during LSP process.
Laser shock peening (LSP) is one of surface treatments to induce residual compressive stresses near metal surface to improve the resistance of materials to surface-related failures, such as fatigue and stress corrosion cracking. In LSP process, short pulsed laser is focused and irradiated to the material covered by transparent overlay such as glass or water. This transparent overlay is also known as a con nement layer and has an important role to increase impact pressure during LSP process. When con nement layer is liquid, the characteristics of the layer such as temperature, viscosity, etc. affect the phenomena occurring during the peening process and undoubtedly in uence the induced residual stress. In the present study, Acoustic Emission (AE) technique coupling with high speed camera was applied to study the effect of con nement layer on LSP process. The results were discussed using the impact force calculated by inverse analysis of detected AE waveforms and bubble parameters observed by high speed camera. The results showed that temperature, thickness and viscosity of con nement layer had strong in uence on the generation and collapse of cavitation bubble. The optimization of process parameters could be obtained by AE technique.
This paper deals with the identification of dynamic parameters included in the modified LuGre model and the identification method is applied to a hydraulic actuator. In order to simulate dynamic behaviors of friction of a hydraulic actuator well, Yanada and Sekikawa have modified the LuGre model by incorporating lubricant film dynamics into the LuGre model and have shown that the dynamic friction behaviors of a hydraulic actuator can be simulated by the modified LuGre model with a relatively good accuracy 10). However, no method to identify the dynamic parameters included in the modified LuGre model has been proposed yet. In this paper, a method to identify the dynamic parameters, i.e., the time constant of lubricating film dynamics and the bristle stiffness is proposed. Using a single rod hydraulic cylinder, friction characteristics are experimentally investigated under various conditions of velocity variation under different supply pressures. The friction force of the hydraulic cylinder is measured based on the equation of motion using measured values of the pressures in the cylinder chambers and the acceleration of the hydraulic piston. Measured friction characteristics are compared with simulated ones by the modified LuGre model. It is shown that the dynamic behaviors of friction simulated using the parameters identified by the proposed method agree relatively well with those obtained by experiments and that the proposed identification method is appropriate. It is also shown that the time constant becomes longer under higher pressures and that the bristle stiffness does not depend on the pressure.
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