The wind–sand climate prevalent in the central and western regions of Inner Mongolia results in significant damage to wind turbine blade coatings due to sand erosion. This not only leads to a decline in power generation but also poses safety risks. This study replicated the wind–sand environment of Alashan and numerically simulated the erosion and wear process of the blade coatings of a 1.5 MW horizontal axis wind turbine under rotational conditions using the DPM model. Additionally, erosion tests were conducted on the operating wind rotor in a wind tunnel. The simulation results demonstrate that sand particle trajectories in the rotating domain are influenced by vortex, incoming wind speed, and sand particle size. For small-sized sand particles, variations in wind speed do not substantially alter the number of particles in contact with the wind turbine blades. However, alterations in the momentum of these particles lead to changes in the impact force on the coating surface. Conversely, the change of wind speed will not only alter the number of large-size sand particles in contact with the wind rotor but also modify the impact force on the coating surface. Furthermore, after impacting the blade, small sand particles continue to move along an approximate helical trajectory with the airflow, while large-size sand particles swiftly rebound. Through statistical analysis of erosion pits on the blade surface after the erosion experiments, it was observed that, in comparison among the leading edge, windward side, trailing edge, and leeward side, the leading edge presents the greatest number of erosion pits, whereas the leeward side has the fewest. Along the spanwise direction, the 0.7R-blade tip segment exhibits the highest count, while the blade root-0.3R section displays the fewest number of pits. The wear morphology of the blade coating was observed from the blade root to tip. The leading edge coating exhibits a range from shallow pits to coating flaking and deeper gouge pits. On the windward side, the coating displays wear patterns varying from tiny cutting pits to cutting marks, and then to gouge pits and coating flaking. Erosion morphology of the trailing edge evolves from only minor scratches to spalling pits, further deepening and enlarging. These research findings provide a basis for the study of zoning-adapted coating materials for wind turbine blades in wind–sand environments.

In recent years, with the gradual expansion of the planting area for Chinese crab apple trees, the traditional method of picking crab apples has become inadequate due to its large workload, low efficiency, and high cost. To address this issue, this paper presents the design of a trunk-type vibration picker specifically for crab apple picking. The design process began with a modal analysis and a harmonic response analysis of a crab apple tree using Ansys Workbench. Through these analyses, the optimal excitation frequency for the crab apple tree was determined to be 12.7 Hz. Subsequently, the picker was designed, and its key components underwent modal and stress analyses. A comparison revealed no resonance between the picker and the key components, ensuring the feasibility of the picker. To further evaluate the performance of the picker, a rigid–flexible coupling analysis was conducted using Adams. This analysis determined the acceleration response curves of the lateral branch points of the crab apple tree at various excitation frequencies: 9.7 Hz, 12.7 Hz, 15.7 Hz, and 18.7 Hz. Finally, field trials were carried out to validate the reliability of the data obtained from Adams. The results showed that the lateral branch point acceleration increased with higher excitation frequencies. However, when the optimal excitation frequency of 12.7 Hz was reached, the lateral branch point acceleration decreased. This indicated that the most effective vibration frequency for picking crab apples was 12.7 Hz.

More and more wind turbines are installed in cold regions because of better wind resources. In these regions, the high humidity and low temperatures in winter will lead to ice accumulation on the wind turbine impeller. A different icing location or mass will lead to different natural frequency variations of the impeller. In order to monitor the icing situation in time and in advance, a method based on depth neural network technology to predict the icing mass is explored and proposed. Natural-environment icing experiments and iced-impeller modal experiments are carried out, aiming at a 600 W wind turbine, respectively. The mapping relationship between the change rate of the natural frequency of the iced impeller at different icing positions and the icing mass is obtained, and the correlation coefficients are all above 0.93. A deep neural network (DNN) prediction model of ice-coating quality for the impeller was constructed with the change rate of the first six-order natural frequencies as the input factor. The results show that the MAE and MSE of the trained model are close to 0. The average prediction error of the DNN model is 4.79%, 9.35%, 3.62%, 1.63%, respectively, under different icing states of the impeller. It can be seen that the DNN shows the best prediction ability among other methods. The smaller the actual ice-covered mass of the impeller, the larger the relative error of the ice-covered mass predicted by the DNN model. In the same ice-covered state, the relative error will decrease gradually with the increase in ice-covered mass. In a word, using the natural frequency change rate to predict the icing quality is feasible and accurate. The research achievements shown here can provide a new idea for wind farms to realize efficient and intelligent icing monitoring and prediction, provide engineering guidance for the wind turbine blade anti-icing and deicing field, and further reduce the negative impact of icing on wind power generation.

Through the mechanical analysis of air-pressure subsoiler, it is found that the main factors affecting its tractive resistance are the air pressure injected into the soil, the soil cohesion, the length and width of the shovel surface, the soil disturbance coefficient, and moving speed of the subsoiler. The traditional air-pressure subsoiler was redesigned to solve the problem of large tractive resistance. In the soil trench experiment, the subsoiling shovel's shape, the air pressure, and the position of air hole were used as test factors, and the ratio of the traction resistance of the shovel to the soil disturbance, namely SDF (Specific Draft Force), was used as the evaluation index. By the response surface test method and analysing the soil disturbance and the tractive resistance, it is determined that rectangular subsoiling shovel with the air hole in the upper part of the shovel is the optimal under the pressure of 1.2 MPa.

1. In recent years, with the rapid development of the global wind energy industry, the proportion of wind farms built in cold and humid regions has been steadily increasing (Li et al., 2022; Liu et...