Parallel kinematic machines, are closed loop structures which have more accuracy, stiffness and ability to withstand high loads. In this paper the vibration equations of the new parallel mechanism, that has higher stiffness because of parallelogram system and fixed length pods, have been derived by analytical approach. Whereas the proposed mechanism is applied as a machine tools, its vibrational behavior investigation has key impact factor. All the kinematic chains of the mechanism have been taken into consideration to achieve the coupled system of equations. To extract mechanism natural frequencies, modal analysis is carried out using three methods including analytical, finite element (FEM) and experimental method on parallel mechanism which has four degrees of freedom including three linear motion along the x, y and z axes and a rotary motion about x axis. Finally the natural frequencies and mode shapes obtained from analytical, experimental and FEM were compared. It is worth noting that all the frequencies obtained from three methods had little differences. تفاصيل المقالة

In this paper, the effects of transverse cracks on rotating shaft were studied. According to earlier works, crack shaft failure decrease the critical speed of the shaft and also exhibit a nonlinear vibration behaviour leading to increases the amplitude of 1X and 2X harmonics (first and second order of rotational speed in torsional vibration). This suggests that the application of order analysis to be very effective. Moreover, vibrations arising from resonance frequencies of the system can be differentiated from other ones, by using this method. For this purpose in this article, first, un cracked and cracked shaft were mathematically modelled and numerical analysis was carried out to obtain the vibration response for both healthy and faulty shaft. Then order analysis method was applied on the vibration signals obtained from the model. Finally, an experiment was also carried out on a laboratory scale test rig to verify effectiveness of the order analysis in practice. The results show that the vibration orders arising from torsional vibration can be clearly sensed by the transducers installed on the supports which primarily measure the bending vibrations. تفاصيل المقالة

Demanding high dimensional accuracy of finished work pieces and reducing the scrap and production cost, call for devising reliable tool condition monitoring system in machining processes. In this paper, a tool wear monitoring system for tool state evaluation during hard turning of AISI D2 is proposed. The method is based on the use of wavelet packet transform for extracting features from vibration signals, followed by neural network for associating the root mean square values of extracted features with tool flank wear values of the cutting tool. From the result of performed experiments, coefficient of determination and root mean square error for the proposed tool wear monitoring system were found to be 99% and 0.0104 respectively. The experimental results show that wavelet packet transform of vibration signals obtained from the cutting tool has high accuracy in tool wear monitoring. Furthermore, the proposed neural network has the acceptable ability in generalizing the system characteristics by predicting values close to the actual measured ones even for the cutting conditions not encountered in the training stage. تفاصيل المقالة