Workload of Composite Bonding Repair Based on Eye Tracking and EEG
Workload is an important influencing factor of airworthiness maintenance errors control and personnel performance improvement in the bonding repair of civil aircraft composite materials.To study the workload,the eye movement and EEG(electrooculogram)generated in the repairing process were used.Firstly,the experimental scene of composite sandwich structure repair was established.Then,the eye movement behaviors and EEG signals were collected in three typical repairing tasks of"damage materials removal","scarf patch materials preparation"and"layering and curing environment construction"and the work performance and workload based on NASA-TLX were calculated.Finally,the feature pattern of"eye movement+EEG"which was significantly related to the workload was extracted by correlation analysis.Based on this pattern,BP neural network and support vector machine method were used to construct the workload prediction model.The results show that with the increase of workload,the level of work performance declines,the fixation time,saccade time,saccade frequency and average saccade frequency are higher,the distribution of fixation hotspots and trajectories are more scattered,the spectral density of EEG power in theta,alpha and beta bands are higher,and the EEG signals in the frontal and temporal lobes of the brain are stronger.The workload predicting model of"eye movement+EEG"feature mode combined with support vector machine method has higher accuracy,which can support the airworthiness maintenance process monitoring of civil aircraft composite materials effectively.
万方数据
维普
