Research On The Occupational Illness Warning Model Of Cumulative Effect

With the growth of our national economy,problems of Chinese occupational gradually became prominent. In recently, there has many early warning models for the occupational illness, but many of them did the estimate for a special working place or a special job, or built the results form the medical statistics. Few of them were did the early warning for an individual person’s whole career from the comprehensive consideration of every pathogenic factor. In the special time of the Chinese occupational health development, it is difficult to estimate the risk of people’s serious occupational illness and hard to give the suggestions. There has no early warning mechanism of occupational illness for individual person so that this paper wants to build an effective early warning mechanism.In this research,an occupational illness warning model will build upon the personal occupational illness risk in his whole career. According the biological cumulative effects concepts, the paper defined the occupational illness scopes form the description of cumulative effects and analyzed the relevant factors which lead to occupational illness; furthermore, built the universal warning way in this research field. Then, as the example of productive dust cause pneumoconiosis, the paper built the occupational illness early warning model with the BP neural network methods which use the four warning factors, just as the inherent risk of enterprise occupational health, the management of enterprise occupational health, the personal unmask situation and the individual difference situation, and realized it with MATLAB. This paper has built an early warning model with cumulative effects for an individual person which will have a great meaning for the occupational illness prevention. In the end of the paper, the paper made a number of occupational illness prevention advice based on the research of current prevention situation.