[Study on the antioxidation property of engine oil by infrared spectroscopy]

The relationship between the engine oil' s infrared spectroscopic characteristics and its antioxidation property was studied, and the technical method to obtain the spectral information in accordance with the contribution of lubricating-oil composition to antioxidation property is presented. Quantitative self-organization neural networks was developed by combining the advantages of BP neural networks and those of self-organization neural networks. Quantitative self-organization neural networks possesses both the qualitative clustering function of self-organization neural networks and the quantitative analysis function of BP neural networks, and featuFes better robustness, so the quantitative analysis result of quantitative self-organization neural networks was better than that of BP neural networks. The result has provided a kind of new technology means for fast testing lubricating-oil performance.