Abstract:
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficiency. In August 2022, we selected a typical coal mine, constructed a comprehensive evaluation index of miners\' occupational health through a questionnaire survey based on the fully connected neural network model. A Bayesian model was used to verify the influence of mechanization level on miners\' occupational health. We found that: the predicted probability of occupational diseases could be used as a comprehensive indicator of the level of occupational health, providing a basis for early intervention and prevention of occupational diseases. Mechanization could directly promote the improvement of miners\' occupational health level, and also indirectly affect occupational health level by influencing hazards level and work intensity. The indirect effect of mechanization on work intensity was positive, and the indirect effect of mechanization on hazards level was positive. Presented the \"inverted U-shaped\" process in the mechanization breakthrough semi-mechanized level would realize the economies of scale of health protection, its impact on the prevention and control of occupational hazards would turn from negative to positive.
探索机械化对矿工职业健康影响的传导机制,为煤炭行业发展健康与高效兼顾的新质生产力提供实证依据,于2022年8月,选择某典型煤矿,通过问卷调查,基于全连接神经网络模型,构建矿工职业健康综合评价指标,并采用贝叶斯模型验证机械化水平对矿工职业健康的影响。研究发现,职业病预测概率可以作为职业健康水平的综合指标,为职业病的早期干预与预防提供依据;机械化水平可以直接促进矿工职业健康水平的提升,也可以通过影响危害因素水平和工作强度来间接影响职业健康水平;机械化水平对工作强度的间接影响是正向的,机械化水平对危害因素水平的间接影响呈现出的\"倒U型\"过程,在机械化水平突破半机械化水平后会实现健康防护的规模经济效应,其对职业危害因素防控的影响会由负转正。.