The following are some common methods for data analysis of the welding quality of automatic hobbing welding machine for electric pole steel skeleton:

1. ** Data collection ** : record the relevant parameters of each welding, such as welding current, voltage, welding time, steel bar diameter, material, etc., and record the quality test results after welding, such as weld appearance defects, strength test data, etc.

2. ** Establish a database ** : Organize and store the collected data in a special database for subsequent analysis.

3. ** Statistical Analysis ** :

- Calculate statistical indicators such as the mean value and standard difference of various parameters to understand the central tendency and degree of dispersion of parameters.

- Comparative analysis of welding quality in different batches and under different conditions.

4. ** Correlation analysis ** : Analyze the correlation between welding parameters and welding quality to determine which parameters have a greater impact on welding quality.

5. ** Trend analysis ** : Observe the changing trend of welding quality with time, process adjustment and other factors to determine whether there are systemic problems or improvement effects.

6. ** Defect classification analysis ** : classification and statistics of weld defects, understanding of the main defect types and their proportion, and taking targeted improvement measures.

7. ** Comparison standard ** : The welding quality data is compared with the relevant standards or specifications to assess whether it meets the requirements.

8. ** Multiple regression analysis ** : If the data is sufficient, you can try to establish a multiple regression model to predict the relationship between welding quality and various parameters in order to better optimize the welding process.