Soft robot has been one significant study in recent decades and soft gripper is one of the popular research directions of soft robot. In a static gripping system, excessive gripping force and large deformation are the main reasons for damage of the object during the gripping process. For achieving low-damage gripping to the object in static gripping system, we proposed a soft-rigid gripper actuated by a linear-extension soft pneumatic actuator in this study. The characteristic of the gripper under a no loading state was measured. When the pressure was >70 kPa, there was an approximately linear relation between the pressure and extension length of the soft actuator. To achieve gripping force and fingertip displacement control of the gripper without sensors integrated on the finger, we presented a non-contact sensing method for gripping state estimation. To analyze the gripping force and fingertip displacement, the relationship between the pressure and extension length of the soft actuator in loading state was compared with the relationship under a no-loading state. The experimental results showed that the relative error between the analytical gripping force and the measured gripping force of the gripper was ≤2.1%. The relative error between analytical fingertip displacement and theoretical fingertip displacement of the gripper was ≤7.4%. Furthermore, the low damage gripping to fragile and soft objects in static and dynamic gripping tests showed good performance of the gripper. Overall, the results indicated the potential application of the gripper in pick-and-place operations.

Accurately obtaining the posture and spatial position of tea buds through machine vision and other technologies is difficult due to the small size, different shapes, and complex growth environment of tea buds. Therefore, end effectors are prone to problems, such as picking omission and picking error. This study designs a picking end effector based on negative pressure guidance for famous tea. This end effector uses negative pressure to guide tea buds in a top-down manner, thereby correcting their posture and spatial position. Therefore, the designed end effector has deviation tolerance performance that can improve the picking success rate. The pre-experiment is designed, the tip of apical bud is referred to as the descent position, and the negative pressure range is determined to be 0.6 to 0.9 kPa. A deviation tolerance orthogonal experiment is designed. Experimental results show that various experimental factors are ranked in terms of the significance level of the effect on the average success rate, and the significance ranking is as follows: negative pressure (P) > pipe diameter (D) > descent speed (V). An evaluation method of deviation tolerance performance is presented, and the optimal experiment factor-level combination is determined as: P = 0.9 kPa, D = 34 mm, V = 20 mm/s. Within the deviation range of a 10 mm radius, the average success rate of the negative pressure guidance of the end effector is 97.36%. The designed end effector can be applied to the intelligent picking of famous tea. This study can provide a reference for the design of similar picking end effectors for famous tea.

In previous studies, the negative impedance electromagnetic shunt damping (EMSD) can increase the damping of host structures to reduce the unexpected vibration. This paper proposes a novel electromagnetic shunt mass (EMSM) concept, which can tune the natural frequency of an electro-mechanical system and simultaneously suppress vibration. The EMSM means that the mass of a system can be controlled with the EMSD. An electromagnetic transducer is designed and modeled. The negative inductance negative resistance (NINR) and the positive inductance negative resistance (PINR) shunts are proposed to investigate the tuning of the natural frequency characteristics. The governing equation of the coupling system is derived, and the EMSM model is established in frequency domain. The optimal resistance and inductance of the shunt are analyzed theoretically, and the root locus is employed to judge the stability of the coupling system. The laboratory experiment was setup to verify the EMSM concept. The results demonstrate that the EMSM can electrically tune the natural frequency of the electromagnetic transducer. Furthermore, the NINR–EMSM has the excellent performance in isolation region, and the PINR–EMSM is more effective to suppress the low frequency vibrations in resonant region.

Due to the complex structure of the angle grinder and the existence of multiple rotating parts, the coupling phenomenon of the data results in the complexity and chaos of the data. The market scale of angle grinder is huge. Manual diagnosis and traditional diagnosis are difficult to meet the requirements, so a fault diagnosis method of angle grinder that is based on adaptive parameters and chaos theory of dual-strategy differential evolution algorithm (ACD-DE) and SVM model hybrid algorithm is proposed by combining a chaos-mapping algorithm, dynamic and adaptive scale factor, and crossover factor. The effectiveness and robustness of the algorithm are proven by solving eight test functions. The acceleration signal is decomposed by wavelet packet decomposition and reconstruction, and a variety of sensor signals are processed and constructed as feature vectors. The training set and the test set of the fault diagnosis model are divided. SVM model is used as the fault diagnosis model and optimized by ACD-DE. Based on the fault data of the angle grinder, the hybrid algorithm is compared with other optimization algorithms and other machine learning models; the comparison results show that the performance of the improved differential evolution algorithm is improved, in which the precision rate is 98.81%, the recall rate is 98.74%, and the F1 score is 0.9877. Experiments show that the hybrid algorithm has strong diagnosis accuracy and robustness.

In-depth analysis of the pressure profile of coating beads of slot die coating is helpful to better understand the behavior of the flow field in a coating bead and to better obtain a stable coating bead. In this study, ANSYS Fluent 19.2 was used to simulate slot die coating. The simulation results clearly show the influence of various operating parameters on the state of the coating bead and the pressure profile in the coating bead. The results show that the pressure profile can be clearly changed by changing the flow rate, substrate speed, and downstream die lip length. Simultaneously increasing the substrate speed from 0.08 to 0.12 m/s and the average inlet velocity from 0.02672 to 0.04 m/s results in an increase in maximum pressure from 298 to 538 Pa. Increasing only the substrate speed, from 0.12 to 0.16 m/s, causes the maximum pressure to decrease from 538 to 195 Pa. Increasing only the average inlet flow velocity, from 0.027 to 0.04 m/s, leads to an increase in maximum pressure from 167 to 745 Pa. Extending the downstream die lip length from 0.4 mm to 1 mm results in an increase in maximum pressure from 189 to 471 Pa. Reducing the upstream coating gap from 0.3 to 0.1 mm results in significant changes in the pressure profile in the upstream direction. Changing the contact angle can affect the pressure profile in the coating bead, but this is not clear. Changing the coating liquid density at a Reynolds number less than 1.733 has less effect on the pressure profile.

Due to the complex shape of the tea tree canopy and the large undulation of a tea garden terrain, the quality of fresh tea leaves harvested by existing tea harvesting machines is poor. This study proposed a tea canopy surface profiling method based on 2D LiDAR perception and investigated the extraction and fitting methods of canopy point clouds. Meanwhile, a tea profiling harvester prototype was developed and field tests were conducted. The tea profiling harvesting device adopted a scheme of sectional arrangement of multiple groups of profiling tea harvesting units, and each unit sensed the height information of its own bottom canopy area through 2D LiDAR. A cross-platform communication network was established, enabling point cloud fitting of tea plant surfaces and accurate estimation of cutter profiling height through the RANSAC algorithm. Additionally, a sensing control system with multiple execution units was developed using rapid control prototype technology. The results of field tests showed that the bud leaf integrity rate was 84.64%, the impurity rate was 5.94%, the missing collection rate was 0.30%, and the missing harvesting rate was 0.68%. Furthermore, 89.57% of the harvested tea could be processed into commercial tea, with 88.34% consisting of young tea shoots with one bud and three leaves or fewer. All of these results demonstrated that the proposed device effectively meets the technical standards for machine-harvested tea and the requirements of standard tea processing techniques. Moreover, compared to other commercial tea harvesters, the proposed tea profiling harvesting device demonstrated improved performance in harvesting fresh tea leaves.