*5.1. Cotton Seeder Duckbill Welding Robot Test Results and Analysis*

The welding wire used in the welding test is a 1.2 mm diameter solid wire (JQ·MG50-6; Tianjin Golden Bridge Welding Materials Group Co., Ltd., Tianjin, China), the protective gas is a mixture of CO2 and argon gas, and the cotton planter duckbill welding robot was tested. The welding process parameters used in the test are shown in Table 3. The cotton seeder duckbill welding robot is shown in Figure 17.

**Table 3.** Welding process parameters.


**Figure 17.** Cotton seeder duckbill welding robot.

The cotton seeder duckbill welding robot factory test photo is shown in Figure 18. The Human Machine Interface (HMI) of the cotton seeder duckbill welding robot is shown in Figure 19. According to the national standard DL/T 868-2004 welding procedure qualification procedure [32], the appearance of the weld after duck beak welding is analyzed. It can be seen from Figure 20 that there are no defects such as unmelted, porosity, and undercutting on the weld surface, and the welding quality is good. After testing, the welding efficiency of the cotton seeder duckbill welding robot is 6–7 times faster than that of the manual, and 600–800 duckbills can be welded per hour. The weld is well-formed. The welding pass rate is 85%, which can meet the needs of practical engineering. The development of the cotton seeder duckbill welding robot will greatly improve the welding efficiency of the duckbill parts and promote the large-scale and standardized production of the duckbill of the cotton seeder. The forming of welding parts is shown in Figure 20. The cotton seeder duckbill welding robot performance comparison is shown in Table 4.

**Figure 18.** Factory test of cotton seeder duckbill welding robot. (**a**) Welding test site; (**b**) welding test in progress.

**Figure 19.** HMI.

**Figure 20.** Welding forming of duckbill parts.


**Table 4.** The cotton seeder duckbill welding robot performance comparison.

#### *5.2. Discussion*

In this paper, a duckbill welding robot for cotton seeder is designed, including the mechanical structure and control system of the welding robot. The efficiency of a cotton seeder duckbill welding robot was greatly improved compared with manual work and semiautomatic welding robots, but there is still unqualified welding in the duckbill welding test. The main reason for this phenomenon is that there are some errors in the manufacturing and assembly of the parts of the duckbill welding robot for the cotton seeder. Mechanical vibration will occur during the operation, which will affect the accuracy of welding parts and the accuracy of welding gun welding. In the follow-up study, improving the welding robot parts manufacturing and assembly accuracy, and further optimizing the structure, will improve the welding robot welding qualification rate.

#### **6. Conclusions**

In this study, the characteristics of the duckbill parts were analyzed first, and then the welding process of the duckbill parts was simulated by Simufact Welding software. The whole process of welding was observed intuitively. At the same time, the deformation and stress changes of the weldment were compared and analyzed when the unilateral single welding torch and the bilateral symmetrical double welding torch, two welding forms, and two welding process parameters, were used. On this basis, a kind of cotton seeder duckbill welding robot was designed, and the welding test was carried out. The results show that the cotton seeder duckbill welding robot has high welding efficiency and good forming quality of welded parts. The design of the cotton seeder duckbill welding robot greatly improves the welding efficiency of the duckbill, which helps to solve the problems of low welding efficiency and unstable welding quality in manual welding and semi-automatic welding robots, and provides a strong guarantee for large-scale and standardized welding production of the duckbill.

**Author Contributions:** Writing—original draft preparation, Y.R.; writing—review and editing, W.G.; resources, X.W.; data curation, C.H.; visualization, L.W.; supervision, X.H. and J.X.; project administration, W.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Bingtuan Science and Technology Program, grant number 2020CB034, and the Innovation research team project of Tarim University, grant number TDZKCX202103.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Acknowledgments:** Thanks for being grateful for the support of the Bingtuan Science and Technology Program (Grant No. 2020CB034), the Innovation research team project of Tarim University (Grant TDZKCX202103). The authors are grateful to anonymous reviewers for their comments.

**Conflicts of Interest:** The authors declare no conflict of interest.
