Research on cognitive load evaluation with subjective method in manual assembly

Subjective scales have different kinds of applicability in diverse fields.This study intends to implement a quantitative approach to determine the applicability of subjective scales in manual as-sembly work and evaluate the cognitive load of assembly workers.A multi-scale research paradigm based on subjective evaluation method is proposed.Three typical task stages are extracted from the process of assembly work.The National Aeronautics and Space Administration Task Load Index(NASA-TLX)scale,PAAS scale and Workload Profile Index Ratings(WP)scale are selected for the design of 3×3 multi-factor mixed experiment.The power spectrum density(PSD)characteris-tics of electroencephalogram(EEG)are utilized to identify the difficulty levels of the three task sta-ges.The relevant indicators of scale applicability are assessed.The results show that in terms of sensitivity,NASA-TLX scale reaches the highest sensitivity(F=999.137,P=0<0.05).In terms of validity,NASA-TLX scale possesses the best concurrent validity(P=0.0255<0.05).In terms of diagnosticity,NASA-TLX scale based on 6 dimensions takes on the best diagnostic performance.In terms of subject acceptability,WP scale performs the worst.According to the analytic hierarchy process(AHP)model,the applicability scores of NASA-TLX scale,PAAS scale and WP scale are determined as 3,2.55 and 1.6714,respectively.Therefore,NASA-TLX scale is regarded as the most suitable subjective evaluation questionnaire for assembly workers,which is also an effective quantitative evaluation method for the cognitive load of assembly workers.

Application of wavelet scale correlation filtering and its improved algorithm in signal processing with a spark sound source

It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm, which is based on adjacent-scale correlation, has limited anti-interference ability due to the low signal-to-noise ratio （SNR） and similar Lipschitz exponent characteristic of each other. However, because different frequency bands of the broadband electric spark signal have different noise interferences, the filtering algorithm based on adjacent-scale correlation is adapted to high SNR and small-scale high-frequency wavelet coefficients filtering; the filtering algorithm based on cross-scale correlation is adapted to low SNR and large-scale low-frequency wavelet coefficients filtering, and the threshold coefficient selection method had been corrected in the algorithm. It is shown that the filtering algorithm has a good filtering effect and extracts the broadband spark sound source signal effectively; it is applicable to broadband underwater acoustic signM processing in the presence of narrow-band strong interference background noise.