Limit oxygen index test method based on logistic regression

In response to the problems of the traditional limit oxygen index determination method, such as the cumbersome operation process, reliance on table lookup for result calculation, which is prone to introducing human errors, and a high dependence on the subjective experience of the operator, which affects the accuracy of the test results, in this paper, the calculation method of logistic regression binary classification is used to establish an oxygen index function model and, through Origin software, to fit the oxygen index function curve to calculate the limit oxygen index. The oxygen index function model was analyzed. The coefficient of determination, R², was 0.6971, with P = 7.3675 × 10⁻¹⁰. The model had good fitting effect and stability. Through a comparison of tests using the logistic regression method and the lookup table method, it was indicated that the logistic regression method effectively shortened the test cycle, and the test results had low dispersion. This method could retain higher stability and consistency under different temperature and humidity conditions. The deviation between the limit oxygen index determined by the logistic regression method and the oxygen index determined by the table lookup method is less than 0.2%. The logistic regression method can be used to effectively avoid the generation of invalid data during the test, improving the traditional method of determining the oxygen index. It is simple to operate, quick in calculation, and accurate in results. This method can be used to effectively and accurately determine the limit oxygen index of textile materials.