Development of Technical staff

Warm congratulations to the first postdoc cultivated by Hengfengtai Postdoctoral Workstation for her outstanding achievements

On December 26, Post-Doc Wen Juan, co-trained by Hengfengtai Precision Machinery Co., Ltd. and Zhejiang University of Technology, "Research on Life Prediction of Precision RV Reducer based on Deep Generative Adversarial Network" project conclusion assessment and review meeting was successfully held in Hengfengtai.

It is understood that Dr. Wen Juan entered the station in December 2020 and successfully passed the mid-term assessment in February 2022. In this concluding report, Dr. Wen Juan elaborated in detail from four aspects: the significance and status quo of the project research, the completed work, the main results, the summary and the prospect.According to reports, RV reducer is the most commonly used reducer at the joint of industrial robots, so to detect its performance state and predict its remaining life has important scientific value and practical application significance. At present, life prediction based on machine learning has been widely used.However, the life test of RV reducer needs to consume a lot of manpower and time, and the amount of data obtained is very limited, which restricts the development and application of RV reducer life prediction technology. To solve the above problems, Dr. Wen Juan proposed the RV reducer life prediction method based on depth-generated adversarial network.During the station, Dr. Wen Juan conducted a life test study on the RV reducer developed by Hengfengtai, and obtained the life cycle data of several groups of reducers. The signal processing method was used to analyze the vibration signal of the reducer. Finally, the experts of the examination committee agreed that Dr. Wen Juan had excellent results and successfully left the station.

 

It is understood that Dr. Wen Juan entered the station in December 2020 and successfully passed the mid-term assessment in February 2022. In this concluding report, Dr. Wen Juan elaborated in detail from four aspects: the significance and status quo of the project research, the completed work, the main results, the summary and the prospect. According to reports, RV reducer is the most commonly used reducer at the joint of industrial robots, so to detect its performance state and predict its remaining life has important scientific value and practical application significance. At present, life prediction based on machine learning has been widely used. However, the life test of RV reducer needs to consume a lot of manpower and time, and the amount of data obtained is very limited, which restricts the development and application of RV reducer life prediction technology. To solve the above problems, Dr. Wen Juan proposed the RV reducer life prediction method based on depth-generated adversarial network. During the station, Dr. Wen Juan conducted a life test study on the RV reducer developed by Hengfengtai, and obtained the life cycle data of several groups of reducers. The signal processing method was used to analyze the vibration signal of the reducer. Finally, the experts of the examination committee agreed that Dr. Wen Juan had excellent results and successfully left the station.