Development of a Human-Machine Interactive Haptic System for PLM Applications for Virtual Product Designing Process
Project no. 1110 · Status: Kapanmış · 2017
Summary
Although all the progress performed regarding virtual product models in the reversible engineering process of PLM, the human cognitive motor ability (feeling) is not included to the loop during during devolopment. In this research, an innovative human-machine interactive PLM haptic system has been designed by including human cognitive motor ability to the process of the virtual product development process. In this haptic approach; it is benefitted from many disciplines such as reversible engineering tools, sensor networks, human nervous system, signal processing techniques, statistical methods, psychophysical procedures and haptic technologies are used. The investigation is performed on bolt loosing system. It is well known that the bolts in engineering systems which are exposed to operational and environmental variability may sometimes loose which sometimes can cause catastrophic consequences. This could be resulted in loss of property/time and even in some circumstances may lead to loss of life. Therefore, there is a growing need to detect the bolt loosening that could be encountered in these technological engineering structures, so that their safety and integrity can be improved. The research has been deployed on a three-storey system constructed with aluminum members in the laboratory medium. The damage simulation scenarios in three-storey structure have been performed by loosening the frame bolts on each floor which cause the nonlinear effects. The structure can slides on rails in lateral direction only and its ground storey has been excited with an electromagnetic shaker vibrating at band limited random frequencies. Accelerometers are attached to the each edges of the floor to acquire the dynamic response of the structure and use their signals for damage diagnosis. Initially, the accelerometers' measurements collected for each state have been organized to represent the suitable bolt loosening configuration. Once, these measurements have been processed and evaluated in statistical pattern recognition algorithms, their performance results have been compared and presented via tables and ROC curves. It is obtained from ROC curves that VAR model coupled with PCA technique has the highest diagnosis performance score in terms of area under curve (AUC) and optimum true positive rate (TPR). Finally, the scores obtained from pattern recognition have been applied to the participants with haptic stimulation, and their perception performance in virtual environment have been tested. As a result, it is observed that the proposed approach may be an effective tool to diagnose the possible damage in product intuitively. Keywords: Virtueal modelling, haptics systems, Bolt loosening, pattern recognition, structural health monitoring, vector-auto regressive models, singular value decomposition, Mahalanobis distance, principal component analysis, environmental and operational uncertainties