Shao Renping

Bio: Shao Renping is an academic researcher from Northwestern Polytechnical University. The author has contributed to research in topics: Cycloid gear & Fault (power engineering). The author has an hindex of 1, co-authored 3 publications receiving 129 citations.

Transmission device for robot joint

Abstract: The invention discloses a transmission device for a robot joint. According to the transmission device for the robot joint, a two-stage small tooth difference cycloidal pin wheel is used for transmission, a pin tooth disc is fixedly connected with an input crankshaft through a first needle bearing, a second cycloidal gear is fixedly connected to the middle of the input crankshaft and is connected with the outer circle of a second needle bearing, a key groove and a hole used for torque transmission are formed in the other end of the input crankshaft, a first cycloidal gear is fixedly connected with transmission crankshafts and is meshed with pin teeth on the pin tooth disc, the second cycloidal gear is meshed with the pin wheel, three trapezoidal holes are evenly distributed in the second cycloidal gear, three trapezoidal protrusions are correspondingly arranged on a supporting disc, the top portions of the trapezoidal protrusions are provided with screw holes and are fixedly connected with an output disc, the three transmission crankshafts drive the supporting disc and the output disc to rotate in the opposite directions at a low speed, the supporting disc is connected with the pin wheel through a main bearing, and multiple output screw holes and multiple output rods are evenly distributed on the output disc and are used for connecting and outputting the torque. According to the transmission device for the robot joint, the two-stage small tooth difference cycloidal pin wheel is used for transmission, and thus the requirements for small size, high speed ratio and large torque of transmission of the robot joint are met.

Novel artificial hand flexible transmission control mechanism

Abstract: The invention discloses a novel artificial hand flexible transmission control mechanism which comprises a planetary gear mechanism, a switching mechanism, an artificial hand and a hand clamp. A planetary gear of the planetary gear mechanism is a duplicate planetary gear, a sun gear is directly matched with an input shaft to serve as an input end, an inner gear is fixed onto a shell of the artificial hand, and a planetary frame serving as an output end is fixedly connected with a sleeve. An outer ring of the switching mechanism is directly fixedly connected with the sleeve through a screw to serve as an input end, a roller is matched with an output shaft to serve as an output end, a shifting fork is connected onto the switching mechanism through a guide post, a guide column slides along a sliding groove under the combined action of an arc push rod and a spring, the artificial hand is driven to flexibly open and close, and reliable, flexible and continuous switching is realized. The artificial hand flexible transmission control mechanism is driven by the duplicate planetary gear, the size is maximally reduced on the premise of meeting the requirement of transmission ratio, meshing overlap ratio is increased, efficiency is improved, and noise is reduced.

A hybrid fault diagnosis method based on second generation wavelet de-noising and local mean decomposition for rotating machinery.

Abstract: In order to extract fault features of large-scale power equipment from strong background noise, a hybrid fault diagnosis method based on the second generation wavelet de-noising (SGWD) and the local mean decomposition (LMD) is proposed in this paper. In this method, a de-noising algorithm of second generation wavelet transform (SGWT) using neighboring coefficients was employed as the pretreatment to remove noise in rotating machinery vibration signals by virtue of its good effect in enhancing the signal-noise ratio (SNR). Then, the LMD method is used to decompose the de-noised signals into several product functions (PFs). The PF corresponding to the faulty feature signal is selected according to the correlation coefficients criterion. Finally, the frequency spectrum is analyzed by applying the FFT to the selected PF. The proposed method is applied to analyze the vibration signals collected from an experimental gearbox and a real locomotive rolling bearing. The results demonstrate that the proposed method has better performances such as high SNR and fast convergence speed than the normal LMD method.