## 6 Conclusions  
Aiming at the existing black box doubly fed wind turbine fault ride-through transient control and parameter identification research engineering application is insufficient. This paper proposes a structured model fault ride-through identification method for black box new energy units based on measured data, which realizes the accurate identification of fault transient control parameters. The conclusions are summarized as follows:  
(1) The fault transient process is analyzed, the three-segment transient process of fault ride-through is divided, and a structured three-segment control model of electromechanical transient for a doubly fed wind turbine is proposed, which specifies the core identification parameters of each control stage in the fault ride-through transient process, and enhances the versatility of the structured model for different turbine types and fault conditions.  
(2) Aiming at the segmentation dynamic control identification needs of the electromechanical transient structured model of a doubly fed wind turbine, a black box new energy turbine fault ride-through parameter identification method based on measured data is proposed. The accuracy and reliability of data segmentation are improved by the data refinement segmentation method based on statistical modal characteristics. Combined with the genetic Newtonian hybrid optimization algorithm, high-precision parameter identification is achieved, which significantly improves the accuracy and robustness of the identification results and provides more reliable theoretical support for the fault ride-through control of doubly fed wind turbines.  
(3) Based on the proposed parameter identification method, a practical joint parameter identification software platform is developed, and simulation tests are carried out by using actual doubly fed wind turbine measured data, and the simulation results verify the effectiveness and accuracy of the proposed parameter identification method and software for different fault types of working conditions, which indicates that it has good engineering application value.  
Conceptualization, X.Z. and S.M.; methodology, S.M.; software, S.M.; validation, X.Z., S.M. and J.Y.; formal analysis, S.M. and Q.W.; investigation, J.Y.; resources, L.G.; data curation, H.H.; writing--original draft preparation, L.G., H.H. and Q.X.; writing--review and editing, S.M. and Q.X.; visualization, Q.W.; supervision, L.B.; project administration, L.B.; funding acquisition, X.Z. and L.B. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Beijing Natural Science Foundation (3232051), the Beijing Natural Science Foundation (L244005),the National Natural Science Foundation of China (52107135), and the Fundamental Research Funds for the Central Universities (2024 ZKPYJ[D07]).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data supporting the findings of this study are included within the article. For further inquiries, please contact the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.